1
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Prokić I, Lahousse L, de Vries M, Liu J, Kalaoja M, Vonk JM, van der Plaat DA, van Diemen CC, van der Spek A, Zhernakova A, Fu J, Ghanbari M, Ala-Korpela M, Kettunen J, Havulinna AS, Perola M, Salomaa V, Lind L, Ärnlöv J, Stricker BHC, Brusselle GG, Boezen HM, van Duijn CM, Amin N. A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease. BMC Pulm Med 2020; 20:193. [PMID: 32677943 PMCID: PMC7364599 DOI: 10.1186/s12890-020-01222-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 06/29/2020] [Indexed: 11/16/2022] Open
Abstract
Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16, P = 5.6 × 10− 4 in the discovery and OR = 1.30, P = 1.8 × 10− 6 in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52–2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94–1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.
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Affiliation(s)
- Ivana Prokić
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Lies Lahousse
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Bioanalysis, Pharmaceutical Care Unit, Ghent University, Ghent, Belgium
| | - Maaike de Vries
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jun Liu
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marita Kalaoja
- Computational Medicine department, Center for Life Course Health Research, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Judith M Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana A van der Plaat
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,National Heart and Lung Institute, Imperial College London, London, UK
| | - Cleo C van Diemen
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ashley van der Spek
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jingyuan Fu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Genetics, School of Medicine,, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mika Ala-Korpela
- Computational Medicine department, Center for Life Course Health Research, Biocenter Oulu, University of Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Johannes Kettunen
- Computational Medicine department, Center for Life Course Health Research, Biocenter Oulu, University of Oulu, Oulu, Finland.,Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aki S Havulinna
- Finnish Institute for Health and Welfare, Helsinki, Finland.,Molecular Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland.,Molecular Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Johan Ärnlöv
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Huddinge, Sweden.,School of Health and Social Sciences, Dalarna University, Falun, Sweden
| | - Bruno H C Stricker
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Guy G Brusselle
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium.,Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Marike Boezen
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, UK
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2
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van der Spek A, Warner SC, Broer L, Nelson CP, Vojinovic D, Ahmad S, Arp PP, Brouwer RWW, Denniff M, van den Hout MCGN, van Rooij JGJ, Kraaij R, van IJcken WFJ, Samani NJ, Ikram MA, Uitterlinden AG, Codd V, Amin N, van Duijn CM. Exome Sequencing Analysis Identifies Rare Variants in ATM and RPL8 That Are Associated With Shorter Telomere Length. Front Genet 2020; 11:337. [PMID: 32425970 PMCID: PMC7204400 DOI: 10.3389/fgene.2020.00337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 03/20/2020] [Indexed: 01/04/2023] Open
Abstract
Telomeres are important for maintaining genomic stability. Telomere length has been associated with aging, disease, and mortality and is highly heritable (∼82%). In this study, we aimed to identify rare genetic variants associated with telomere length using whole-exome sequence data. We studied 1,303 participants of the Erasmus Rucphen Family (ERF) study, 1,259 of the Rotterdam Study (RS), and 674 of the British Heart Foundation Family Heart Study (BHF-FHS). We conducted two analyses, first we analyzed the family-based ERF study and used the RS and BHF-FHS for replication. Second, we combined the summary data of the three studies in a meta-analysis. Telomere length was measured by quantitative polymerase chain reaction in blood. We identified nine rare variants significantly associated with telomere length (p-value < 1.42 × 10–7, minor allele frequency of 0.2–0.5%) in the ERF study. Eight of these variants (in C11orf65, ACAT1, NPAT, ATM, KDELC2, and EXPH5) were located on chromosome 11q22.3 that contains ATM, a gene involved in telomere maintenance. Although we were unable to replicate the variants in the RS and BHF-FHS (p-value ≥ 0.21), segregation analysis showed that all variants segregate with shorter telomere length in a family. In the meta-analysis of all studies, a nominally significant association with LTL was observed with a rare variant in RPL8 (p-value = 1.48 × 10−6), which has previously been associated with age. Additionally, a novel rare variant in the known RTEL1 locus showed suggestive evidence for association (p-value = 1.18 × 10–4) with LTL. To conclude, we identified novel rare variants associated with telomere length. Larger samples size are needed to confirm these findings and to identify additional variants.
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Affiliation(s)
- Ashley van der Spek
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,SkylineDx B.V., Rotterdam, Netherlands
| | - Sophie C Warner
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | - Linda Broer
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Pascal P Arp
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Rutger W W Brouwer
- Center for Biomics, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | | | - Jeroen G J van Rooij
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Neurology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Wilfred F J van IJcken
- Center for Biomics, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom.,NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
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3
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Sharapov SZ, Tsepilov YA, Klaric L, Mangino M, Thareja G, Shadrina AS, Simurina M, Dagostino C, Dmitrieva J, Vilaj M, Vuckovic F, Pavic T, Stambuk J, Trbojevic-Akmacic I, Kristic J, Simunovic J, Momcilovic A, Campbell H, Doherty M, Dunlop MG, Farrington SM, Pucic-Bakovic M, Gieger C, Allegri M, Louis E, Georges M, Suhre K, Spector T, Williams FMK, Lauc G, Aulchenko YS. Defining the genetic control of human blood plasma N-glycome using genome-wide association study. Hum Mol Genet 2019; 28:2062-2077. [PMID: 31163085 PMCID: PMC6664388 DOI: 10.1093/hmg/ddz054] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 03/01/2019] [Accepted: 03/06/2019] [Indexed: 01/10/2023] Open
Abstract
Glycosylation is a common post-translational modification of proteins. Glycosylation is associated with a number of human diseases. Defining genetic factors altering glycosylation may provide a basis for novel approaches to diagnostic and pharmaceutical applications. Here we report a genome-wide association study of the human blood plasma N-glycome composition in up to 3811 people measured by Ultra Performance Liquid Chromatography (UPLC) technology. Starting with the 36 original traits measured by UPLC, we computed an additional 77 derived traits leading to a total of 113 glycan traits. We studied associations between these traits and genetic polymorphisms located on human autosomes. We discovered and replicated 12 loci. This allowed us to demonstrate an overlap in genetic control between total plasma protein and IgG glycosylation. The majority of revealed loci contained genes that encode enzymes directly involved in glycosylation (FUT3/FUT6, FUT8, B3GAT1, ST6GAL1, B4GALT1, ST3GAL4, MGAT3 and MGAT5) and a known regulator of plasma protein fucosylation (HNF1A). However, we also found loci that could possibly reflect other more complex aspects of glycosylation process. Functional genomic annotation suggested the role of several genes including DERL3, CHCHD10, TMEM121, IGH and IKZF1. The hypotheses we generated may serve as a starting point for further functional studies in this research area.
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Affiliation(s)
- Sodbo Zh Sharapov
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
| | - Yakov A Tsepilov
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, UK
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UK
| | - Gaurav Thareja
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | | | - Mirna Simurina
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Concetta Dagostino
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, Parma, Italy
| | - Julia Dmitrieva
- Unit of Animal Genomics, WELBIO, GIGA-R and Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Marija Vilaj
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Frano Vuckovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Tamara Pavic
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Jerko Stambuk
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | | | - Jasminka Kristic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Jelena Simunovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Ana Momcilovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Margaret Doherty
- Institute of Technology Sligo, Department of Life Sciences, Sligo, Ireland
- National Institute for Bioprocessing Research & Training, Dublin, Ireland
| | - Malcolm G Dunlop
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Susan M Farrington
- Colon Cancer Genetics Group, MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Maja Pucic-Bakovic
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
| | - Christian Gieger
- Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Centre Munich, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, Germany
| | - Massimo Allegri
- Pain Therapy Department, Policlinico Monza Hospital, Monza, Italy
| | - Edouard Louis
- CHU-Liège and Unit of Gastroenterology, GIGA-R and Faculty of Medicine, University of Liège, 1 Avenue de l’Hôpital, Liège, Belgium
| | - Michel Georges
- Unit of Animal Genomics, WELBIO, GIGA-R and Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Tim Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
| | - Frances M K Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, St Thomas’ Campus, London, UK
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, Zagreb, Croatia
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovacica 1, Zagreb, Croatia
| | - Yurii S Aulchenko
- Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, Russia
- Novosibirsk State University, 1, Pirogova str., Novosibirsk, Russia
- PolyOmica, Het Vlaggeschip 61, PA 's-Hertogenbosch, The Netherlands
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4
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Chen N, Juric I, Cosgrove EJ, Bowman R, Fitzpatrick JW, Schoech SJ, Clark AG, Coop G. Allele frequency dynamics in a pedigreed natural population. Proc Natl Acad Sci U S A 2019; 116:2158-2164. [PMID: 30598449 PMCID: PMC6369762 DOI: 10.1073/pnas.1813852116] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
A central goal of population genetics is to understand how genetic drift, natural selection, and gene flow shape allele frequencies through time. However, the actual processes underlying these changes-variation in individual survival, reproductive success, and movement-are often difficult to quantify. Fully understanding these processes requires the population pedigree, the set of relationships among all individuals in the population through time. Here, we use extensive pedigree and genomic information from a long-studied natural population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of different evolutionary processes in shaping patterns of genetic variation through time. We performed gene dropping simulations to estimate individual genetic contributions to the population and model drift on the known pedigree. We found that observed allele frequency changes are generally well predicted by accounting for the different genetic contributions of founders. Our results show that the genetic contribution of recent immigrants is substantial, with some large allele frequency shifts that otherwise may have been attributed to selection actually due to gene flow. We identified a few SNPs under directional short-term selection after appropriately accounting for gene flow. Using models that account for changes in population size, we partitioned the proportion of variance in allele frequency change through time. Observed allele frequency changes are primarily due to variation in survival and reproductive success, with gene flow making a smaller contribution. This study provides one of the most complete descriptions of short-term evolutionary change in allele frequencies in a natural population to date.
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Affiliation(s)
- Nancy Chen
- Center for Population Biology, University of California, Davis, CA 95616;
- Department of Evolution & Ecology, University of California, Davis, CA 95616
- Department of Biology, University of Rochester, Rochester, NY 14627
| | - Ivan Juric
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195
| | - Elissa J Cosgrove
- Department of Molecular Biology & Genetics, Cornell University, Ithaca, NY 14850
| | - Reed Bowman
- Avian Ecology Program, Archbold Biological Station, Venus, FL 33960
| | | | - Stephan J Schoech
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152
| | - Andrew G Clark
- Department of Molecular Biology & Genetics, Cornell University, Ithaca, NY 14850
| | - Graham Coop
- Center for Population Biology, University of California, Davis, CA 95616
- Department of Evolution & Ecology, University of California, Davis, CA 95616
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5
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Liu F, Chen Y, Zhu G, Hysi PG, Wu S, Adhikari K, Breslin K, Pospiech E, Hamer MA, Peng F, Muralidharan C, Acuna-Alonzo V, Canizales-Quinteros S, Bedoya G, Gallo C, Poletti G, Rothhammer F, Bortolini MC, Gonzalez-Jose R, Zeng C, Xu S, Jin L, Uitterlinden AG, Ikram MA, van Duijn CM, Nijsten T, Walsh S, Branicki W, Wang S, Ruiz-Linares A, Spector TD, Martin NG, Medland SE, Kayser M. Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair. Hum Mol Genet 2019; 27:559-575. [PMID: 29220522 PMCID: PMC5886212 DOI: 10.1093/hmg/ddx416] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 11/29/2017] [Indexed: 01/18/2023] Open
Abstract
Shape variation of human head hair shows striking variation within and between human populations, while its genetic basis is far from being understood. We performed a series of genome-wide association studies (GWASs) and replication studies in a total of 28 964 subjects from 9 cohorts from multiple geographic origins. A meta-analysis of three European GWASs identified 8 novel loci (1p36.23 ERRFI1/SLC45A1, 1p36.22 PEX14, 1p36.13 PADI3, 2p13.3 TGFA, 11p14.1 LGR4, 12q13.13 HOXC13, 17q21.2 KRTAP, and 20q13.33 PTK6), and confirmed 4 previously known ones (1q21.3 TCHH/TCHHL1/LCE3E, 2q35 WNT10A, 4q21.21 FRAS1, and 10p14 LINC00708/GATA3), all showing genome-wide significant association with hair shape (P < 5e-8). All except one (1p36.22 PEX14) were replicated with nominal significance in at least one of the 6 additional cohorts of European, Native American and East Asian origins. Three additional previously known genes (EDAR, OFCC1, and PRSS53) were confirmed at the nominal significance level. A multivariable regression model revealed that 14 SNPs from different genes significantly and independently contribute to hair shape variation, reaching a cross-validated AUC value of 0.66 (95% CI: 0.62–0.70) and an AUC value of 0.64 in an independent validation cohort, providing an improved accuracy compared with a previous model. Prediction outcomes of 2504 individuals from a multiethnic sample were largely consistent with general knowledge on the global distribution of hair shape variation. Our study thus delivers target genes and DNA variants for future functional studies to further evaluate the molecular basis of hair shape in humans.
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Affiliation(s)
- Fan Liu
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,University of Chinese Academy of Sciences, Beijing, China
| | - Yan Chen
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Pirro G Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sijie Wu
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kaustubh Adhikari
- Department of Genetics, Evolution, and Environment, University College London, London WC1E 6BT, UK
| | - Krystal Breslin
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Ewelina Pospiech
- Institute of Zoology and Biomedical Research, Faculty of Biology and Earth Sciences, Jagiellonian University, Kraków, Poland.,Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Fuduan Peng
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Charanya Muralidharan
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Victor Acuna-Alonzo
- Laboratorio de Genética Molecular, Escuela Nacional de Antropologia e Historia, México City, México
| | - Samuel Canizales-Quinteros
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, México City, México
| | - Gabriel Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, Colombia
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | | | - Maria Catira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil
| | - Rolando Gonzalez-Jose
- Instituto Patagónico de Ciencias Sociales y Humanas, CENPAT-CONICET, Puerto Madryn, Argentina
| | - Changqing Zeng
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Shuhua Xu
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Li Jin
- University of Chinese Academy of Sciences, Beijing, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Susan Walsh
- Department of Biology, Indiana-University-Purdue-University-Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.,Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Sijia Wang
- University of Chinese Academy of Sciences, Beijing, China.,Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Andrés Ruiz-Linares
- Department of Genetics, Evolution, and Environment, University College London, London WC1E 6BT, UK.,Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai, China.,Laboratory of Biocultural Anthropology, Law, Ethics, and Health (Centre National de la Recherche Scientifique and Etablissement Français du Sang), Aix-Marseille Université, Marseille, France
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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6
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Vojinovic D, Kavousi M, Ghanbari M, Brouwer RWW, van Rooij JGJ, van den Hout MCGN, Kraaij R, van Ijcken WFJ, Uitterlinden AG, van Duijn CM, Amin N. Whole-Genome Linkage Scan Combined With Exome Sequencing Identifies Novel Candidate Genes for Carotid Intima-Media Thickness. Front Genet 2018; 9:420. [PMID: 30356672 PMCID: PMC6189289 DOI: 10.3389/fgene.2018.00420] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 09/10/2018] [Indexed: 01/06/2023] Open
Abstract
Carotid intima-media thickness (cIMT) is an established heritable marker for subclinical atherosclerosis. In this study, we aim to identify rare variants with large effects driving differences in cIMT by performing genome-wide linkage analysis of individuals in the extremes of cIMT trait distribution (>90th percentile) in a large family-based study from a genetically isolated population in the Netherlands. Linked regions were subsequently explored by fine-mapping using exome sequencing. We observed significant evidence of linkage on chromosomes 2p16.3 [rs1017418, heterogeneity LOD (HLOD) = 3.35], 19q13.43 (rs3499, HLOD = 9.09), 20p13 (rs1434789, HLOD = 4.10), and 21q22.12 (rs2834949, HLOD = 3.59). Fine-mapping using exome sequencing data identified a non-coding variant (rs62165235) in PNPT1 gene under the linkage peak at chromosome 2 that is likely to have a regulatory function. The variant was associated with quantitative cIMT in the family-based study population (effect = 0.27, p-value = 0.013). Furthermore, we identified several genes under the linkage peak at chromosome 21 highly expressed in tissues relevant for atherosclerosis. To conclude, our linkage analysis identified four genomic regions significantly linked to cIMT. Further analyses are needed to demonstrate involvement of identified candidate genes in development of atherosclerosis.
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Affiliation(s)
- Dina Vojinovic
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands.,Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Rutger W W Brouwer
- Department of Cell Biology, Center for Biomics, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Jeroen G J van Rooij
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Mirjam C G N van den Hout
- Department of Cell Biology, Center for Biomics, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Wilfred F J van Ijcken
- Department of Cell Biology, Center for Biomics, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands.,Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands.,Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
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7
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Yao Y, Xu Y, Zhao J, Ma Y, Su K, Yuan W, Ma JZ, Payne TJ, Li MD. Detection of Significant Association Between Variants in Cannabinoid Receptor 1 Gene ( CNR1) and Personality in African-American Population. Front Genet 2018; 9:199. [PMID: 29963071 PMCID: PMC6010580 DOI: 10.3389/fgene.2018.00199] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 05/17/2018] [Indexed: 12/31/2022] Open
Abstract
Background: Several studies have revealed significant associations between single nucleotide polymorphisms (SNPs) in the cannabinoid receptor 1 (CNR1) gene and a broad spectrum of psychiatric disorders such as major depressive disorder (MDD), attention deficit hyperactivity disorder (ADHD), and schizophrenia. Personality traits that are highly related to susceptibility to these conditions have been associated with the CNR1 variants in subjects of Caucasian origin. However, there are no reported studies regarding the effects of CNR1 polymorphisms on personality traits in the African-American (AA) population. Methods: We performed an imputation-based association analysis for 26 CNR1 variants with five dimensions of personality in 3,046 AAs. Results: SNPs rs806372 and rs2180619 showed a significant association with extraversion after Bonferroni correction for multiple testing (p < 0.0019). Further, several extraversion-associated SNPs were significantly associated with conscientiousness, agreeableness, and openness. SNP priority score analysis indicated that SNPs rs806368, rs806371, and rs2180619 play a role in the modulation of personality and psychiatric conditions. Conclusion:CNR1 is important in determining personality traits in the AA population.
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Affiliation(s)
- Yinghao Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Yi Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Junsheng Zhao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Yunlong Ma
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Kunkai Su
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenji Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China
| | - Jennie Z Ma
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States
| | - Thomas J Payne
- Department of Otolaryngology and Communicative Sciences, University of Mississippi Medical Center, Jackson, MS, United States
| | - Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, Hangzhou, China.,Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China.,Institute of Neuroimmune Pharmacology, Seton Hall University, South Orange, NJ, United States
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8
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A rare missense variant in RCL1 segregates with depression in extended families. Mol Psychiatry 2018; 23:1120-1126. [PMID: 28322274 PMCID: PMC5984098 DOI: 10.1038/mp.2017.49] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Revised: 01/27/2017] [Accepted: 01/30/2017] [Indexed: 02/07/2023]
Abstract
Depression is the most prevalent psychiatric disorder with a complex and elusive etiology that is moderately heritable. Identification of genes would greatly facilitate the elucidation of the biological mechanisms underlying depression, however, its complex etiology has proved to be a major bottleneck in the identification of its genetic risk factors, especially in genome-wide association-like studies. In this study, we exploit the properties of a genetic isolate and its family-based structure to explore whether relatively rare exonic variants influence the burden of depressive symptoms in families. Using a multistep approach involving linkage and haplotype analyses followed by exome sequencing in the Erasmus Rucphen Family (ERF) study, we identified a rare (minor allele frequency (MAF)=1%) missense c.1114C>T mutation (rs115482041) in the RCL1 gene segregating with depression across multiple generations. Rs115482041 showed significant association with depressive symptoms (N=2393, βT-allele=2.33, P-value=1 × 10-4) and explained 2.9% of the estimated genetic variance of depressive symptoms (22%) in ERF. Despite being twice as rare (MAF<0.5%), c.1114C>T showed similar effect and significant association with depressive symptoms in samples from the independent population-based Rotterdam study (N=1604, βT-allele=3.60, P-value=3 × 10-2). A comparison of RCL1 expression in human and mouse brain revealed a striking co-localization of RCL1 with the layer 1 interlaminar subclass of astrocytes found exclusively in higher-order primates. Our findings identify RCL1 as a novel candidate gene for depression and offer insights into mechanisms through which RCL1 may be relevant for depression.
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9
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Nedeljkovic I, Terzikhan N, Vonk JM, van der Plaat DA, Lahousse L, van Diemen CC, Hobbs BD, Qiao D, Cho MH, Brusselle GG, Postma DS, Boezen HM, van Duijn CM, Amin N. A Genome-Wide Linkage Study for Chronic Obstructive Pulmonary Disease in a Dutch Genetic Isolate Identifies Novel Rare Candidate Variants. Front Genet 2018; 9:133. [PMID: 29725345 PMCID: PMC5916965 DOI: 10.3389/fgene.2018.00133] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/03/2018] [Indexed: 01/06/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein (AHNAK), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 (PLCB3), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 (SLC22A11), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 (MTL5), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.
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Affiliation(s)
- Ivana Nedeljkovic
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Judith M. Vonk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Diana A. van der Plaat
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lies Lahousse
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Pharmaceutical Care Unit, Department of Bioanalysis, Ghent University, Ghent, Belgium
| | - Cleo C. van Diemen
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Brian D. Hobbs
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Guy G. Brusselle
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - Dirkje S. Postma
- Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Department of Pulmonary Medicine and Tuberculosis, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - H. M. Boezen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Groningen Research Institute for Asthma and COPD, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | | | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
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10
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Silva CT, Zorkoltseva IV, Niemeijer MN, van den Berg ME, Amin N, Demirkan A, van Leeuwen E, Iglesias AI, Piñeros-Hernández LB, Restrepo CM, Kors JA, Kirichenko AV, Willemsen R, Oostra BA, Stricker BH, Uitterlinden AG, Axenovich TI, van Duijn CM, Isaacs A. A combined linkage, microarray and exome analysis suggests MAP3K11 as a candidate gene for left ventricular hypertrophy. BMC Med Genomics 2018; 11:22. [PMID: 29506515 PMCID: PMC5838853 DOI: 10.1186/s12920-018-0339-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 02/21/2018] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Electrocardiographic measures of left ventricular hypertrophy (LVH) are used as predictors of cardiovascular risk. We combined linkage and association analyses to discover novel rare genetic variants involved in three such measures and two principal components derived from them. METHODS The study was conducted among participants from the Erasmus Rucphen Family Study (ERF), a Dutch family-based sample from the southwestern Netherlands. Variance components linkage analyses were performed using Merlin. Regions of interest (LOD > 1.9) were fine-mapped using microarray and exome sequence data. RESULTS We observed one significant LOD score for the second principal component on chromosome 15 (LOD score = 3.01) and 12 suggestive LOD scores. Several loci contained variants identified in GWAS for these traits; however, these did not explain the linkage peaks, nor did other common variants. Exome sequence data identified two associated variants after multiple testing corrections were applied. CONCLUSIONS We did not find common SNPs explaining these linkage signals. Exome sequencing uncovered a relatively rare variant in MAPK3K11 on chromosome 11 (MAF = 0.01) that helped account for the suggestive linkage peak observed for the first principal component. Conditional analysis revealed a drop in LOD from 2.01 to 0.88 for MAP3K11, suggesting that this variant may partially explain the linkage signal at this chromosomal location. MAP3K11 is related to the JNK pathway and is a pro-apoptotic kinase that plays an important role in the induction of cardiomyocyte apoptosis in various pathologies, including LVH.
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Affiliation(s)
- Claudia Tamar Silva
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), GENIUROS Research group, School of Medicine and Health Science, Universidad del Rosario, Bogotá, Colombia
- Doctoral Program in Biomedical Sciences, Universidad del Rosario, Bogotá, Colombia
| | | | - Maartje N. Niemeijer
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marten E. van den Berg
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ayşe Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Elisa van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Adriana I. Iglesias
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Laura B. Piñeros-Hernández
- Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), GENIUROS Research group, School of Medicine and Health Science, Universidad del Rosario, Bogotá, Colombia
| | - Carlos M. Restrepo
- Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), GENIUROS Research group, School of Medicine and Health Science, Universidad del Rosario, Bogotá, Colombia
| | - Jan A. Kors
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Rob Willemsen
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ben A. Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Center for Medical Systems Biology, Leiden, the Netherlands
| | - Bruno H. Stricker
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
- Inspectorate of Health care, The Hague, the Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Center for Medical Systems Biology, Leiden, the Netherlands
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), and Department of Biochemistry, Maastricht University, Maastricht, the Netherlands
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11
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Dolby GA, Hechinger R, Ellingson RA, Findley LT, Lorda J, Jacobs DK. Sea-level driven glacial-age refugia and post-glacial mixing on subtropical coasts, a palaeohabitat and genetic study. Proc Biol Sci 2017; 283:rspb.2016.1571. [PMID: 27903870 DOI: 10.1098/rspb.2016.1571] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 10/31/2016] [Indexed: 11/12/2022] Open
Abstract
Using a novel combination of palaeohabitat modelling and genetic mixture analyses, we identify and assess a sea-level-driven recolonization process following the Last Glacial Maximum (LGM). Our palaeohabitat modelling reveals dramatic changes in estuarine habitat distribution along the coast of California (USA) and Baja California (Mexico). At the LGM (approx. 20 kya), when sea level was approximately 130 m lower, the palaeo-shoreline was too steep for tidal estuarine habitat formation, eliminating this habitat type from regions where it is currently most abundant, and limiting such estuaries to a northern and a southern refugium separated by 1000 km. We assess the recolonization of estuaries formed during post-LGM sea-level rise through examination of refugium-associated alleles and approximate Bayesian computation in three species of estuarine fishes. Results reveal sourcing of modern populations from both refugia, which admix in the newly formed habitat between the refuges. We infer a dramatic peak in habitat area between 15 and 10 kya with subsequent decline. Overall, this approach revealed a previously undocumented dynamic and integrated relationship between sea-level change, coastal processes and population genetics. These results extend glacial refugial dynamics to unglaciated subtropical coasts and have significant implications for biotic response to predicted sea-level rise.
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Affiliation(s)
- Greer A Dolby
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Ryan Hechinger
- Scripps Institution of Oceanography-Marine Biology Research Division, UC San Diego, La Jolla, CA 92093-0218, USA
| | - Ryan A Ellingson
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Lloyd T Findley
- Centro de Investigación en Alimentación y Desarrollo, A.C.-Unidad Guaymas, Carretera al Varadero Nacional km. 6.6, Colonia Las Playitas, Guaymas, Sonora 85480, México
| | - Julio Lorda
- Facultad de Ciencias, Universidad Autónoma de Baja California. Carretera Transpeninsular Ensenada - Tijuana No. 3917, Colonia Playitas, C.P. 22860, Ensenada, Baja California, México
| | - David K Jacobs
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
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12
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van der Spek A, Luik AI, Kocevska D, Liu C, Brouwer RWW, van Rooij JGJ, van den Hout MCGN, Kraaij R, Hofman A, Uitterlinden AG, van IJcken WFJ, Gottlieb DJ, Tiemeier H, van Duijn CM, Amin N. Exome-Wide Meta-Analysis Identifies Rare 3'-UTR Variant in ERCC1/CD3EAP Associated with Symptoms of Sleep Apnea. Front Genet 2017; 8:151. [PMID: 29093733 PMCID: PMC5651235 DOI: 10.3389/fgene.2017.00151] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 09/28/2017] [Indexed: 12/30/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common sleep breathing disorder associated with an increased risk of cardiovascular and cerebrovascular diseases and mortality. Although OSA is fairly heritable (~40%), there have been only few studies looking into the genetics of OSA. In the present study, we aimed to identify genetic variants associated with symptoms of sleep apnea by performing a whole-exome sequence meta-analysis of symptoms of sleep apnea in 1,475 individuals of European descent. We identified 17 rare genetic variants with at least suggestive evidence of significance. Replication in an independent dataset confirmed the association of a rare genetic variant (rs2229918; minor allele frequency = 0.3%) with symptoms of sleep apnea (p-valuemeta = 6.98 × 10−9, βmeta = 0.99). Rs2229918 overlaps with the 3′ untranslated regions of ERCC1 and CD3EAP genes on chromosome 19q13. Both genes are expressed in tissues in the neck area, such as the tongue, muscles, cartilage and the trachea. Further, CD3EAP is localized in the nucleus and mitochondria and involved in the tumor necrosis factor-alpha/nuclear factor kappa B signaling pathway. Our results and biological functions of CD3EAP/ERCC1 genes suggest that the 19q13 locus is interesting for further OSA research.
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Affiliation(s)
| | - Annemarie I Luik
- Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Desana Kocevska
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, Netherlands
| | - Chunyu Liu
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, United States.,Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, United States.,Department of Biostatistics, School of Public Health, Boston University, Boston, MA, United States
| | | | - Jeroen G J van Rooij
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands.,Netherlands Consortium for Healthy Ageing, Rotterdam, Netherlands.,Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands
| | | | - Robert Kraaij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.,Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands.,Netherlands Consortium for Healthy Ageing, Rotterdam, Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.,Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.,Department of Internal Medicine, Erasmus Medical Center, Rotterdam, Netherlands.,Netherlands Consortium for Healthy Ageing, Rotterdam, Netherlands
| | | | - Daniel J Gottlieb
- VA Boston Healthcare System, Boston, MA, United States.,Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA, United States.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.,Department of Psychiatry, Erasmus Medical Center, Rotterdam, Netherlands
| | | | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
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13
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Vojinovic D, Brison N, Ahmad S, Noens I, Pappa I, Karssen LC, Tiemeier H, van Duijn CM, Peeters H, Amin N. Variants in TTC25 affect autistic trait in patients with autism spectrum disorder and general population. Eur J Hum Genet 2017; 25:982-987. [PMID: 28513607 DOI: 10.1038/ejhg.2017.82] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 04/03/2017] [Accepted: 04/13/2017] [Indexed: 12/30/2022] Open
Abstract
Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder with a complex genetic architecture. To identify genetic variants underlying ASD, we performed single-variant and gene-based genome-wide association studies using a dense genotyping array containing over 2.3 million single-nucleotide variants in a discovery sample of 160 families with at least one child affected with non-syndromic ASD using a binary (ASD yes/no) phenotype and a quantitative autistic trait. Replication of the top findings was performed in Psychiatric Genomics Consortium and Erasmus Rucphen Family (ERF) cohort study. Significant association of quantitative autistic trait was observed with the TTC25 gene at 17q21.2 (effect size=10.2, P-value=3.4 × 10-7) in the gene-based analysis. The gene also showed nominally significant association in the cohort-based ERF study (effect=1.75, P-value=0.05). Meta-analysis of discovery and replication improved the association signal (P-valuemeta=1.5 × 10-8). No genome-wide significant signal was observed in the single-variant analysis of either the binary ASD phenotype or the quantitative autistic trait. Our study has identified a novel gene TTC25 to be associated with quantitative autistic trait in patients with ASD. The replication of association in a cohort-based study and the effect estimate suggest that variants in TTC25 may also be relevant for broader ASD phenotype in the general population. TTC25 is overexpressed in frontal cortex and testis and is known to be involved in cilium movement and thus an interesting candidate gene for autistic trait.
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Affiliation(s)
- Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Nathalie Brison
- Center for Human Genetics, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ilse Noens
- Leuven Autism Research (LAuRes), Leuven, Belgium.,Parenting and Special Education Research Unit, KU Leuven, Leuven, Belgium
| | - Irene Pappa
- School of Pedagogical and Educational Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lennart C Karssen
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.,PolyOmica, s-Hertogenbosch, The Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.,Leiden Academic Centre for Drug Research (LACDR), Leiden University, The Netherlands
| | - Hilde Peeters
- Center for Human Genetics, University Hospitals Leuven, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), Leuven, Belgium
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
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14
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Amin N, Jovanova O, Adams HHH, Dehghan A, Kavousi M, Vernooij MW, Peeters RP, de Vrij FMS, van der Lee SJ, van Rooij JGJ, van Leeuwen EM, Chaker L, Demirkan A, Hofman A, Brouwer RWW, Kraaij R, Willems van Dijk K, Hankemeier T, van Ijcken WFJ, Uitterlinden AG, Niessen WJ, Franco OH, Kushner SA, Ikram MA, Tiemeier H, van Duijn CM. Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms. Mol Psychiatry 2017; 22:537-543. [PMID: 27431295 DOI: 10.1038/mp.2016.101] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 04/19/2016] [Accepted: 04/20/2016] [Indexed: 11/09/2022]
Abstract
Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10-08, β=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10-03, β=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.
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Affiliation(s)
- N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - O Jovanova
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - H H H Adams
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - A Dehghan
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - M Kavousi
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - M W Vernooij
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - R P Peeters
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Rotterdam Thyroid Center, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - F M S de Vrij
- Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - S J van der Lee
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - J G J van Rooij
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - E M van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - L Chaker
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Rotterdam Thyroid Center, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - A Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Human Genetics, Leiden University Medical Center, RC Leiden, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - R W W Brouwer
- Center for Biomics, Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands
| | - R Kraaij
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - K Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, RC Leiden, The Netherlands.,Division of Endocrinology, Department of Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - T Hankemeier
- Leiden Academic Center for Drug Research, Division of Analytical Biosciences, Leiden University, Leiden, The Netherlands.,The Netherlands Metabolomics Centre, Leiden University, Leiden, The Netherlands
| | - W F J van Ijcken
- Center for Biomics, Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - W J Niessen
- Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.,Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - O H Franco
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - S A Kushner
- Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - C M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
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15
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Jansen IE, Ye H, Heetveld S, Lechler MC, Michels H, Seinstra RI, Lubbe SJ, Drouet V, Lesage S, Majounie E, Gibbs JR, Nalls MA, Ryten M, Botia JA, Vandrovcova J, Simon-Sanchez J, Castillo-Lizardo M, Rizzu P, Blauwendraat C, Chouhan AK, Li Y, Yogi P, Amin N, van Duijn CM, Morris HR, Brice A, Singleton AB, David DC, Nollen EA, Jain S, Shulman JM, Heutink P. Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing. Genome Biol 2017; 18:22. [PMID: 28137300 PMCID: PMC5282828 DOI: 10.1186/s13059-017-1147-9] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Accepted: 01/03/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.
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Affiliation(s)
- Iris E. Jansen
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, 1081HZ The Netherlands
| | - Hui Ye
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Sasja Heetveld
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Marie C. Lechler
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
- Graduate School of Cellular & Molecular Neuroscience, Tübingen, 72074 Germany
| | - Helen Michels
- European Research Institute for the Biology of Aging, University of Groningen, University Medical Centre Groningen, Groningen, 9700AD The Netherlands
| | - Renée I. Seinstra
- European Research Institute for the Biology of Aging, University of Groningen, University Medical Centre Groningen, Groningen, 9700AD The Netherlands
| | - Steven J. Lubbe
- Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK
- Northwestern University Feinberg School of Medicine, Ken and Ruth Davee Department of Neurology, Chicago, IL USA
| | - Valérie Drouet
- Inserm U1127, CNRS UMR7225, Sorbonne Universités, UPMC Univ Paris 06, UMR_S1127, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Suzanne Lesage
- Inserm U1127, CNRS UMR7225, Sorbonne Universités, UPMC Univ Paris 06, UMR_S1127, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Elisa Majounie
- Institute of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - J. Raphael Gibbs
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD USA
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD USA
| | - Mina Ryten
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Department of Medical & Molecular Genetics, King’s College London, London, UK
| | - Juan A. Botia
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Jana Vandrovcova
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Javier Simon-Sanchez
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Melissa Castillo-Lizardo
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Patrizia Rizzu
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Cornelis Blauwendraat
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Amit K. Chouhan
- Department of Neurology, Baylor College of Medicine, Houston, TX USA
| | - Yarong Li
- Department of Neurology, Baylor College of Medicine, Houston, TX USA
| | - Puja Yogi
- Department of Neurology, Baylor College of Medicine, Houston, TX USA
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Huw R. Morris
- Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK
| | - Alexis Brice
- Inserm U1127, CNRS UMR7225, Sorbonne Universités, UPMC Univ Paris 06, UMR_S1127, Institut du Cerveau et de la Moelle épinière, Paris, France
- Assistance Publique Hôpitaux de Paris, Hôpital de la Salpêtrière, Département de Génétique et Cytogénétique, Paris, France
| | | | - Della C. David
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Ellen A. Nollen
- European Research Institute for the Biology of Aging, University of Groningen, University Medical Centre Groningen, Groningen, 9700AD The Netherlands
| | - Shushant Jain
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
| | - Joshua M. Shulman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- Department of Neurology, Baylor College of Medicine, Houston, TX USA
- Department of Neuroscience and Program in Developmental Biology, Baylor College of Medicine, Houston, TX USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund St., N.1150, Houston, TX 77030 USA
| | - Peter Heutink
- German Center for Neurodegenerative Diseases (DZNE), Otfried-Müller-Str. 23, Tübingen, 72076 Germany
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, 1081HZ The Netherlands
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
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16
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Silva CT, Zorkoltseva IV, Amin N, Demirkan A, van Leeuwen EM, Kors JA, van den Berg M, Stricker BH, Uitterlinden AG, Kirichenko AV, Witteman JCM, Willemsen R, Oostra BA, Axenovich TI, van Duijn CM, Isaacs A. A Combined Linkage and Exome Sequencing Analysis for Electrocardiogram Parameters in the Erasmus Rucphen Family Study. Front Genet 2016; 7:190. [PMID: 27877193 PMCID: PMC5099142 DOI: 10.3389/fgene.2016.00190] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 10/11/2016] [Indexed: 12/30/2022] Open
Abstract
Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the FCRL2 gene associated with QT (rs74608430; P = 2.8 × 10-4, minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait’s genetic variability in ERF (P = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca2+ levels (P = 3.3 × 10-3) and AMPK stimulated fatty acid oxidation in muscle (P = 4.1 × 10-3). Look-ups in bioinformatics resources showed that expression of FCRL2 is associated with ARHGAP24 and SETBP1 expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, FCRL2 emerges as a strong candidate gene for QT interval.
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Affiliation(s)
- Claudia T Silva
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Doctoral Program in Biomedical Sciences, Universidad del RosarioBogotá, Colombia; GENIUROS Group, Genetics and Genomics Research Center CIGGUR, School of Medicine and Health Sciences, Universidad del RosarioBogotá, Colombia
| | - Irina V Zorkoltseva
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center Rotterdam, Netherlands
| | - Ayşe Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Department of Human Genetics, Leiden University Medical CenterLeiden, Netherlands
| | - Elisabeth M van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center Rotterdam, Netherlands
| | - Jan A Kors
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Marten van den Berg
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Department of Internal Medicine, Erasmus University Medical CenterRotterdam, Netherlands; Inspectorate of Health CareThe Hague, Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam, Netherlands
| | - Anatoly V Kirichenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | | | - Rob Willemsen
- Department of Clinical Genetics, Erasmus University Medical Center Rotterdam, Netherlands
| | - Ben A Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
| | - Tatiana I Axenovich
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences Novosibirsk, Russia
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical CenterRotterdam, Netherlands; Center for Medical Systems BiologyLeiden, Netherlands
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17
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Associations with intraocular pressure across Europe: The European Eye Epidemiology (E 3) Consortium. Eur J Epidemiol 2016; 31:1101-1111. [PMID: 27613171 PMCID: PMC5206267 DOI: 10.1007/s10654-016-0191-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2016] [Accepted: 08/07/2016] [Indexed: 11/22/2022]
Abstract
Raised intraocular pressure (IOP) is the most important risk factor for developing glaucoma, the second commonest cause of blindness globally. Understanding associations with IOP and variations in IOP between countries may teach us about mechanisms underlying glaucoma. We examined cross-sectional associations with IOP in 43,500 European adults from 12 cohort studies belonging to the European Eye Epidemiology (E3) consortium. Each study conducted multivariable linear regression with IOP as the outcome variable and results were pooled using random effects meta-analysis. The association of standardized study IOP with latitude was tested using meta-regression. Higher IOP was observed in men (0.18 mmHg; 95 % CI 0.06, 0.31; P = 0.004) and with higher body mass index (0.21 mmHg per 5 kg/m2; 95 % CI 0.14, 0.28; P < 0.001), shorter height (−0.17 mmHg per 10 cm; 95 % CI –0.25, −0.08; P < 0.001), higher systolic blood pressure (0.17 mmHg per 10 mmHg; 95 % CI 0.12, 0.22; P < 0.001) and more myopic refraction (0.06 mmHg per Dioptre; 95 % CI 0.03, 0.09; P < 0.001). An inverted U-shaped trend was observed between age and IOP, with IOP increasing up to the age of 60 and decreasing in participants older than 70 years. We found no significant association between standardized IOP and study location latitude (P = 0.76). Novel findings of our study include the association of lower IOP in taller people and an inverted-U shaped association of IOP with age. We found no evidence of significant variation in IOP across Europe. Despite the limited range of latitude amongst included studies, this finding is in favour of collaborative pooling of data from studies examining environmental and genetic determinants of IOP in Europeans.
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18
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Ponomarenko MP, Arkova O, Rasskazov D, Ponomarenko P, Savinkova L, Kolchanov N. Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters. Front Immunol 2016; 7:130. [PMID: 27092142 PMCID: PMC4819121 DOI: 10.3389/fimmu.2016.00130] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 03/21/2016] [Indexed: 12/17/2022] Open
Abstract
Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine.
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Affiliation(s)
- Mikhail P. Ponomarenko
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
- Novosibirsk State University, Novosibirsk, Russia
| | - Olga Arkova
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
| | - Dmitry Rasskazov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
| | | | - Ludmila Savinkova
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
| | - Nikolay Kolchanov
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
- Novosibirsk State University, Novosibirsk, Russia
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19
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Yu B, Pulit SL, Hwang SJ, Brody JA, Amin N, Auer PL, Bis JC, Boerwinkle E, Burke GL, Chakravarti A, Correa A, Dreisbach AW, Franco OH, Ehret GB, Franceschini N, Hofman A, Lin DY, Metcalf GA, Musani SK, Muzny D, Palmas W, Raffel L, Reiner A, Rice K, Rotter JI, Veeraraghavan N, Fox E, Guo X, North KE, Gibbs RA, van Duijn CM, Psaty BM, Levy D, Newton-Cheh C, Morrison AC. Rare Exome Sequence Variants in CLCN6 Reduce Blood Pressure Levels and Hypertension Risk. ACTA ACUST UNITED AC 2015; 9:64-70. [PMID: 26658788 DOI: 10.1161/circgenetics.115.001215] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 12/10/2015] [Indexed: 11/16/2022]
Abstract
BACKGROUND Rare genetic variants influence blood pressure (BP). METHODS AND RESULTS Whole-exome sequencing was performed on DNA samples from 17 956 individuals of European ancestry and African ancestry (14 497, first-stage discovery and 3459, second-stage discovery) to examine the effect of rare variants on hypertension and 4 BP traits: systolic BP, diastolic BP, pulse pressure, and mean arterial pressure. Tests of ≈170 000 common variants (minor allele frequency, ≥1%; statistical significance, P≤2.9×10(-7)) and gene-based tests of rare variants (minor allele frequency, <1%; ≈17 000 genes; statistical significance, P≤1.5×10(-6)) were evaluated for each trait and ancestry, followed by multiethnic meta-analyses. In the first-stage discovery, rare coding variants (splicing, stop-gain, stop-loss, nonsynonymous variants, or indels) in CLCN6 were associated with lower diastolic BP (cumulative minor allele frequency, 1.3%; β=-3.20; P=4.1×10(-6)) and were independent of a nearby common variant (rs17367504) previously associated with BP. CLCN6 rare variants were also associated with lower systolic BP (β=-4.11; P=2.8×10(-4)), mean arterial pressure (β=-3.50; P=8.9×10(-6)), and reduced hypertension risk (odds ratio, 0.72; P=0.017). Meta-analysis of the 2-stage discovery samples showed that CLCN6 was associated with lower diastolic BP at exome-wide significance (cumulative minor allele frequency, 1.1%; β=-3.30; P=5.0×10(-7)). CONCLUSIONS These findings implicate the effect of rare coding variants in CLCN6 in BP variation and offer new insights into BP regulation.
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20
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Liu F, Hamer MA, Heilmann S, Herold C, Moebus S, Hofman A, Uitterlinden AG, Nöthen MM, van Duijn CM, Nijsten TE, Kayser M. Prediction of male-pattern baldness from genotypes. Eur J Hum Genet 2015; 24:895-902. [PMID: 26508577 DOI: 10.1038/ejhg.2015.220] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 08/27/2015] [Accepted: 09/01/2015] [Indexed: 01/21/2023] Open
Abstract
The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.
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Affiliation(s)
- Fan Liu
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Stefanie Heilmann
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.,Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Christine Herold
- German Center for Neurodegenerative Disease (DZNE), Bonn, Germany
| | - Susanne Moebus
- Institute of Medical Informatics, Biometry, and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Markus M Nöthen
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.,Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tamar Ec Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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21
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Heritabilities, proportions of heritabilities explained by GWAS findings, and implications of cross-phenotype effects on PR interval. Hum Genet 2015; 134:1211-9. [PMID: 26385552 PMCID: PMC4628620 DOI: 10.1007/s00439-015-1595-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Accepted: 08/21/2015] [Indexed: 12/04/2022]
Abstract
Electrocardiogram (ECG) measurements are a powerful tool for evaluating cardiac function and are widely used for the diagnosis and prediction of a variety of conditions, including myocardial infarction, cardiac arrhythmias, and sudden cardiac death. Recently, genome-wide association studies (GWASs) identified a large number of genes related to ECG parameter variability, specifically for the QT, QRS, and PR intervals. The aims of this study were to establish the heritability of ECG traits, including indices of left ventricular hypertrophy, and to directly assess the proportion of those heritabilities explained by GWAS variants. These analyses were conducted in a large, Dutch family-based cohort study, the Erasmus Rucphen Family study using variance component methods implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) software package. Heritability estimates ranged from 34 % for QRS and Cornell voltage product to 49 % for 12-lead sum. Trait-specific GWAS findings for each trait explained a fraction of their heritability (17 % for QRS, 4 % for QT, 2 % for PR, 3 % for Sokolow–Lyon index, and 4 % for 12-lead sum). The inclusion of all ECG-associated single nucleotide polymorphisms explained an additional 6 % of the heritability of PR. In conclusion, this study shows that, although GWAS explain a portion of ECG trait variability, a large amount of heritability remains to be explained. In addition, larger GWAS for PR are likely to detect loci already identified, particularly those observed for QRS and 12-lead sum.
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22
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Genome-wide association analysis on five isolated populations identifies variants of the HLA-DOA gene associated with white wine liking. Eur J Hum Genet 2015; 23:1717-22. [PMID: 25758996 DOI: 10.1038/ejhg.2015.34] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Revised: 01/23/2015] [Accepted: 02/04/2015] [Indexed: 12/19/2022] Open
Abstract
Wine is the most popular alcoholic beverage around the world and because of its importance in society has been widely studied. Understanding what drives its flavor has been a quest for decades but much is still unknown and will be determined at least in part by individual taste preferences. Recently studies in the genetics of taste have uncovered the role of different genes in the determination of food preferences giving new insight on its physiology. In this context we have performed a genome-wide association study on red and white wine liking using three isolated populations collected in Italy, and replicated our results on two additional populations coming from the Netherland and Central Asia for a total of 3885 samples. We have found a significant association (P=2.1 × 10(-8)) between white wine liking and rs9276975:C>T a polymorphism in the HLA-DOA gene encoding a non-canonical MHC II molecule, which regulates other MHC II molecules. The same association was also found with red wine liking (P=8.3 × 10(-6)). Sex-separated analysis have also revealed that the effect of HLA-DOA is twice as large in women as compared to men suggesting an interaction between this polymorphism and gender. Our results are one of the first examples of genome-wide association between liking of a commonly consumed food and gene variants. Moreover, our results suggest a role of the MHC system in the determination of food preferences opening new insight in this field in general.
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23
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van Leeuwen EM, Karssen LC, Deelen J, Isaacs A, Medina-Gomez C, Mbarek H, Kanterakis A, Trompet S, Postmus I, Verweij N, van Enckevort DJ, Huffman JE, White CC, Feitosa MF, Bartz TM, Manichaikul A, Joshi PK, Peloso GM, Deelen P, van Dijk F, Willemsen G, de Geus EJ, Milaneschi Y, Penninx BWJH, Francioli LC, Menelaou A, Pulit SL, Rivadeneira F, Hofman A, Oostra BA, Franco OH, Mateo Leach I, Beekman M, de Craen AJM, Uh HW, Trochet H, Hocking LJ, Porteous DJ, Sattar N, Packard CJ, Buckley BM, Brody JA, Bis JC, Rotter JI, Mychaleckyj JC, Campbell H, Duan Q, Lange LA, Wilson JF, Hayward C, Polasek O, Vitart V, Rudan I, Wright AF, Rich SS, Psaty BM, Borecki IB, Kearney PM, Stott DJ, Adrienne Cupples L, Jukema JW, van der Harst P, Sijbrands EJ, Hottenga JJ, Uitterlinden AG, Swertz MA, van Ommen GJB, de Bakker PIW, Eline Slagboom P, Boomsma DI, Wijmenga C, van Duijn CM. Genome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels. Nat Commun 2015; 6:6065. [PMID: 25751400 PMCID: PMC4366498 DOI: 10.1038/ncomms7065] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Accepted: 12/09/2014] [Indexed: 01/13/2023] Open
Abstract
Variants associated with blood lipid levels may be population-specific. To identify
low-frequency variants associated with this phenotype, population-specific reference
panels may be used. Here we impute nine large Dutch biobanks (~35,000
samples) with the population-specific reference panel created by the Genome of the
Netherlands Project and perform association testing with blood lipid levels. We
report the discovery of five novel associations at four loci (P value
<6.61 × 10−4), including a rare missense
variant in ABCA6
(rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious.
The frequency of this ABCA6
variant is 3.65-fold increased in the Dutch and its effect
(βLDL-C=0.135,
βTC=0.140) is estimated to be very similar to those
observed for single variants in well-known lipid genes, such as LDLR. Frequencies of rare variants fluctuate over populations, hampering
gene discovery. Here the authors use a population-specific reference panel, the Genome
of the Netherlands, to discover four novel loci involved in lipid metabolism, including
an exonic variant in ABCA6.
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Affiliation(s)
| | - Lennart C Karssen
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Carolina Medina-Gomez
- Department of Epidemiology and Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, VU University Amsterdam and EMGO+ Institute for Health and Care Research, Amsterdam 1081BT, The Netherlands
| | - Alexandros Kanterakis
- Department of Genetics, Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, The Netherlands
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Iris Postmus
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
| | | | - Jennifer E Huffman
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Charles C White
- Department of Biostatistics, Boston U School of Public Health, Boston, Massachusetts 02118, USA
| | - Mary F Feitosa
- Department of Genetics, Washington University School of Medicine, St Louis, Missouri 63108, USA
| | - Traci M Bartz
- Department of Biostatistics and Medicine, University of Washington, Seattle, Washington 98101, USA
| | - Ani Manichaikul
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA
| | - Peter K Joshi
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland EH8 9AG, UK
| | - Gina M Peloso
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02176, USA
| | - Patrick Deelen
- Department of Genetics, Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, The Netherlands
| | - Freerk van Dijk
- Department of Genetics, Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam and EMGO+ Institute for Health and Care Research, Amsterdam 1081BT, The Netherlands
| | - Eco J de Geus
- Department of Biological Psychology, VU University Amsterdam and EMGO+ Institute for Health and Care Research, Amsterdam 1081BT, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, VU University Medical Center Amsterdam/GGZinGeest, EMGO+ Institute for Health and Care Research, Neuroscience Campus Amsterdam, Amsterdam 1081HL, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, VU University Medical Center Amsterdam/GGZinGeest, EMGO+ Institute for Health and Care Research, Neuroscience Campus Amsterdam, Amsterdam 1081HL, The Netherlands
| | - Laurent C Francioli
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands
| | - Androniki Menelaou
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands
| | - Sara L Pulit
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology and Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Ben A Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Irene Mateo Leach
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Anton J M de Craen
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Hae-Won Uh
- Department of Genetical Statistics, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Holly Trochet
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Lynne J Hocking
- Division of Applied Health Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, University of Glasgow, Glasgow G12 8QQ, UK
| | - Chris J Packard
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Brendan M Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - Jennifer A Brody
- Department of Medicine, University of Washington, Seattle, Washington 98101, USA
| | - Joshua C Bis
- Department of Medicine, University of Washington, Seattle, Washington 98101, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - Josyf C Mychaleckyj
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland EH8 9AG, UK
| | - Qing Duan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina NC 27599, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina NC 27599, USA
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland EH8 9AG, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split 21000, Croatia
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, Scotland EH8 9AG, UK
| | - Alan F Wright
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Stephen S Rich
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA
| | - Bruce M Psaty
- Department of Medicine and Epidemiology, University of Washington, Seattle, Washington 98101, USA
| | - Ingrid B Borecki
- Department of Genetics and Biostatistics, Washington University School of Medicine, St Louis, Missouri 63108, USA
| | - Patricia M Kearney
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - L Adrienne Cupples
- 1] Department of Biostatistics, Boston U School of Public Health, Boston, Massachusetts 02118, USA [2] Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | | | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
| | - Eric J Sijbrands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam and EMGO+ Institute for Health and Care Research, Amsterdam 1081BT, The Netherlands
| | - Andre G Uitterlinden
- Department of Epidemiology and Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
| | - Morris A Swertz
- Department of Genetics, Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, The Netherlands
| | - Gert-Jan B van Ommen
- Department of Human Genetics, Leiden University Medical Center, Leiden P.O. Box 9600, 2300 RC, The Netherlands
| | - Paul I W de Bakker
- 1] Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands [2] Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht 3584 CG, The Netherlands
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300 RC, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam 1081BT, The Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, The Netherlands
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24
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Li Q, Wojciechowski R, Simpson CL, Hysi PG, Verhoeven VJM, Ikram MK, Höhn R, Vitart V, Hewitt AW, Oexle K, Mäkelä KM, MacGregor S, Pirastu M, Fan Q, Cheng CY, St Pourcain B, McMahon G, Kemp JP, Northstone K, Rahi JS, Cumberland PM, Martin NG, Sanfilippo PG, Lu Y, Wang YX, Hayward C, Polašek O, Campbell H, Bencic G, Wright AF, Wedenoja J, Zeller T, Schillert A, Mirshahi A, Lackner K, Yip SP, Yap MKH, Ried JS, Gieger C, Murgia F, Wilson JF, Fleck B, Yazar S, Vingerling JR, Hofman A, Uitterlinden A, Rivadeneira F, Amin N, Karssen L, Oostra BA, Zhou X, Teo YY, Tai ES, Vithana E, Barathi V, Zheng Y, Siantar RG, Neelam K, Shin Y, Lam J, Yonova-Doing E, Venturini C, Hosseini SM, Wong HS, Lehtimäki T, Kähönen M, Raitakari O, Timpson NJ, Evans DM, Khor CC, Aung T, Young TL, Mitchell P, Klein B, van Duijn CM, Meitinger T, Jonas JB, Baird PN, Mackey DA, Wong TY, Saw SM, Pärssinen O, Stambolian D, Hammond CJ, Klaver CCW, Williams C, Paterson AD, Bailey-Wilson JE, Guggenheim JA. Genome-wide association study for refractive astigmatism reveals genetic co-determination with spherical equivalent refractive error: the CREAM consortium. Hum Genet 2015; 134:131-46. [PMID: 25367360 PMCID: PMC4291519 DOI: 10.1007/s00439-014-1500-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 09/30/2014] [Indexed: 11/24/2022]
Abstract
To identify genetic variants associated with refractive astigmatism in the general population, meta-analyses of genome-wide association studies were performed for: White Europeans aged at least 25 years (20 cohorts, N = 31,968); Asian subjects aged at least 25 years (7 cohorts, N = 9,295); White Europeans aged <25 years (4 cohorts, N = 5,640); and all independent individuals from the above three samples combined with a sample of Chinese subjects aged <25 years (N = 45,931). Participants were classified as cases with refractive astigmatism if the average cylinder power in their two eyes was at least 1.00 diopter and as controls otherwise. Genome-wide association analysis was carried out for each cohort separately using logistic regression. Meta-analysis was conducted using a fixed effects model. In the older European group the most strongly associated marker was downstream of the neurexin-1 (NRXN1) gene (rs1401327, P = 3.92E-8). No other region reached genome-wide significance, and association signals were lower for the younger European group and Asian group. In the meta-analysis of all cohorts, no marker reached genome-wide significance: The most strongly associated regions were, NRXN1 (rs1401327, P = 2.93E-07), TOX (rs7823467, P = 3.47E-07) and LINC00340 (rs12212674, P = 1.49E-06). For 34 markers identified in prior GWAS for spherical equivalent refractive error, the beta coefficients for genotype versus spherical equivalent, and genotype versus refractive astigmatism, were highly correlated (r = -0.59, P = 2.10E-04). This work revealed no consistent or strong genetic signals for refractive astigmatism; however, the TOX gene region previously identified in GWAS for spherical equivalent refractive error was the second most strongly associated region. Analysis of additional markers provided evidence supporting widespread genetic co-susceptibility for spherical and astigmatic refractive errors.
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Affiliation(s)
- Qing Li
- National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive Suite 1200, Baltimore, MD 21224 USA
| | - Robert Wojciechowski
- National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive Suite 1200, Baltimore, MD 21224 USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
- Wilmer Eye Institute, Johns Hopkins Medical Institutions, Baltimore, MD USA
| | - Claire L. Simpson
- National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive Suite 1200, Baltimore, MD 21224 USA
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital Campus, London, UK
| | - Virginie J. M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Mohammad Kamran Ikram
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - René Höhn
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
- Klinik Pallas, Olten, Switzerland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Alex W. Hewitt
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Konrad Oexle
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Kari-Matti Mäkelä
- Department of Clinical Chemistry, Filmlab laboratories, Tampere University Hospital and School of Medicine, University of Tampere, 33520 Tampere, Finland
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute Royal Brisbane Hospital, Brisbane, Australia
| | - Mario Pirastu
- Institute of Population Genetics CNR, Traversa La Crucca, 3-07040 Reg. Baldinca, Li Punti, Sassari, Italy
| | - Qiao Fan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Beaté St Pourcain
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - George McMahon
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - John P. Kemp
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - Kate Northstone
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - Jugnoo S. Rahi
- Centre of Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
- Institute of Ophthalmology, University College London, London, UK
- Ulverscroft Vision Research Group, UCL Institute of Child Health, London, UK
| | - Phillippa M. Cumberland
- Centre of Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
- Ulverscroft Vision Research Group, UCL Institute of Child Health, London, UK
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute Royal Brisbane Hospital, Brisbane, Australia
| | - Paul G. Sanfilippo
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Yi Lu
- Statistical Genetics, QIMR Berghofer Medical Research Institute Royal Brisbane Hospital, Brisbane, Australia
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital University of Medical Science, Beijing, China
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Ozren Polašek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG UK
| | - Goran Bencic
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb, Croatia
| | - Alan F. Wright
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Juho Wedenoja
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Tanja Zeller
- University Heart Center Hamburg, Clinic for general and interventional Cardiology, Hamburg, Germany
| | - Arne Schillert
- Institute for Medical Biometry and Statistics, Universität zu Lübeck, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Hamburg/Kiel/Lübeck, Lübeck, Germany
| | - Alireza Mirshahi
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
- Dardenne Eye Hospital, Bonn, Germany
| | - Karl Lackner
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Mainz, Germany
| | - Shea Ping Yip
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong SAR, China
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Maurice K. H. Yap
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Federico Murgia
- Institute of Population Genetics CNR, Traversa La Crucca, 3-07040 Reg. Baldinca, Li Punti, Sassari, Italy
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG UK
| | - Brian Fleck
- Princess Alexandra Eye Pavilion, Edinburgh, EH3 9HA UK
| | - Seyhan Yazar
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | | | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, The Netherlands
| | - André Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Lennart Karssen
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Xin Zhou
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Eranga Vithana
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Neuroscience and Behavioural Disorders (NBD) Program, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Veluchamy Barathi
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | | | | | - Kumari Neelam
- Singapore Eye Research Institute, Singapore, Singapore
| | - Youchan Shin
- Singapore Eye Research Institute, Singapore, Singapore
| | - Janice Lam
- Singapore Eye Research Institute, Singapore, Singapore
| | - Ekaterina Yonova-Doing
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital Campus, London, UK
| | - Cristina Venturini
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital Campus, London, UK
- Institute of Ophthalmology, University College London, London, UK
| | - S. Mohsen Hosseini
- Genetics and Genome Biology Program, The Hospital for Sick Children Research Institute, PGCRL Rm 12.9835, 686 Bay Street, Toronto, ON M5G 0A4 Canada
| | - Hoi-Suen Wong
- Genetics and Genome Biology Program, The Hospital for Sick Children Research Institute, PGCRL Rm 12.9835, 686 Bay Street, Toronto, ON M5G 0A4 Canada
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Filmlab laboratories, Tampere University Hospital and School of Medicine, University of Tampere, 33520 Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and School of Medicine, University of Tampere, 33521 Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20041 Turku, Finland
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - David M. Evans
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
- Translational Research Institute, University of Queensland Diamantina Institute, Brisbane, QLD Australia
| | - Chiea-Chuen Khor
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Tin Aung
- Singapore Eye Research Institute, Singapore, Singapore
| | - Terri L. Young
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
- Duke Eye Center, Duke University School of Medicine, Durham, NC USA
| | - Paul Mitchell
- University of Sydney, Sydney, Australia
- Western Sydney Local Health Network, Sydney, Australia
- Westmead Millennium Institute, Westmead, Australia
| | - Barbara Klein
- Ophthalmology and Visual Sciences, Ocular Epidemiology, University of Wisconsin-Madison, 610 North Walnut Street, Room 409, Madison, WI 53726 USA
| | | | - Thomas Meitinger
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Jost B. Jonas
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, Germany
| | - Paul N. Baird
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - David A. Mackey
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Seang-Mei Saw
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Olavi Pärssinen
- Department of Health Sciences and Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland
| | - Dwight Stambolian
- University of Pennsylvania School of Medicine, Rm. 314 Stellar Chance Labs, 422 Curie Blvd, Philadelphia, PA 19104 USA
| | - Christopher J. Hammond
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital Campus, London, UK
- Department of Ophthalmology, King’s College London, St Thomas’ Hospital Campus, London, UK
| | - Caroline C. W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
| | - Andrew D. Paterson
- Genetics and Genome Biology Program, The Hospital for Sick Children Research Institute, PGCRL Rm 12.9835, 686 Bay Street, Toronto, ON M5G 0A4 Canada
- Dala Lanna School of Public Health, University of Toronto, Toronto, ON Canada
| | - Joan E. Bailey-Wilson
- National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive Suite 1200, Baltimore, MD 21224 USA
| | - Jeremy A. Guggenheim
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - The CREAM Consortium
- National Human Genome Research Institute, National Institutes of Health, 333 Cassell Drive Suite 1200, Baltimore, MD 21224 USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
- Wilmer Eye Institute, Johns Hopkins Medical Institutions, Baltimore, MD USA
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital Campus, London, UK
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Singapore Eye Research Institute, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
- Klinik Pallas, Olten, Switzerland
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Department of Clinical Chemistry, Filmlab laboratories, Tampere University Hospital and School of Medicine, University of Tampere, 33520 Tampere, Finland
- Statistical Genetics, QIMR Berghofer Medical Research Institute Royal Brisbane Hospital, Brisbane, Australia
- Institute of Population Genetics CNR, Traversa La Crucca, 3-07040 Reg. Baldinca, Li Punti, Sassari, Italy
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN UK
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN UK
- Centre of Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
- Institute of Ophthalmology, University College London, London, UK
- Ulverscroft Vision Research Group, UCL Institute of Child Health, London, UK
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute Royal Brisbane Hospital, Brisbane, Australia
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital University of Medical Science, Beijing, China
- Faculty of Medicine, University of Split, Split, Croatia
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, EH8 9AG UK
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb, Croatia
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
- University Heart Center Hamburg, Clinic for general and interventional Cardiology, Hamburg, Germany
- Institute for Medical Biometry and Statistics, Universität zu Lübeck, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Hamburg/Kiel/Lübeck, Lübeck, Germany
- Dardenne Eye Hospital, Bonn, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Mainz, Germany
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong SAR, China
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Princess Alexandra Eye Pavilion, Edinburgh, EH3 9HA UK
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
- Department of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
- Neuroscience and Behavioural Disorders (NBD) Program, Duke-NUS Graduate Medical School, Singapore, Singapore
- Genetics and Genome Biology Program, The Hospital for Sick Children Research Institute, PGCRL Rm 12.9835, 686 Bay Street, Toronto, ON M5G 0A4 Canada
- Department of Clinical Physiology, Tampere University Hospital and School of Medicine, University of Tampere, 33521 Tampere, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20041 Turku, Finland
- Translational Research Institute, University of Queensland Diamantina Institute, Brisbane, QLD Australia
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
- Duke Eye Center, Duke University School of Medicine, Durham, NC USA
- University of Sydney, Sydney, Australia
- Western Sydney Local Health Network, Sydney, Australia
- Westmead Millennium Institute, Westmead, Australia
- Ophthalmology and Visual Sciences, Ocular Epidemiology, University of Wisconsin-Madison, 610 North Walnut Street, Room 409, Madison, WI 53726 USA
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, Germany
- Department of Health Sciences and Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland
- University of Pennsylvania School of Medicine, Rm. 314 Stellar Chance Labs, 422 Curie Blvd, Philadelphia, PA 19104 USA
- Department of Ophthalmology, King’s College London, St Thomas’ Hospital Campus, London, UK
- Dala Lanna School of Public Health, University of Toronto, Toronto, ON Canada
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25
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The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels. PLoS One 2014; 9:e109290. [PMID: 25329471 PMCID: PMC4203717 DOI: 10.1371/journal.pone.0109290] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Accepted: 08/29/2014] [Indexed: 11/23/2022] Open
Abstract
Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10−8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.
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26
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Vojinovic D, Adams HHH, van der Lee SJ, Ibrahim-Verbaas CA, Brouwer R, van den Hout MCGN, Oole E, van Rooij J, Uitterlinden A, Hofman A, van IJcken WFJ, Aartsma-Rus A, van Ommen GB, Ikram MA, van Duijn CM, Amin N. The dystrophin gene and cognitive function in the general population. Eur J Hum Genet 2014; 23:837-43. [PMID: 25227141 DOI: 10.1038/ejhg.2014.183] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Revised: 08/04/2014] [Accepted: 08/10/2014] [Indexed: 12/26/2022] Open
Abstract
The aim of our study is to investigate whether single-nucleotide dystrophin gene (DMD) variants associate with variability in cognitive functions in healthy populations. The study included 1240 participants from the Erasmus Rucphen family (ERF) study and 1464 individuals from the Rotterdam Study (RS). The participants whose exomes were sequenced and who were assessed for various cognitive traits were included in the analysis. To determine the association between DMD variants and cognitive ability, linear (mixed) modeling with adjustment for age, sex and education was used. Moreover, Sequence Kernel Association Test (SKAT) was used to test the overall association of the rare genetic variants present in the DMD with cognitive traits. Although no DMD variant surpassed the prespecified significance threshold (P<1 × 10(-4)), rs147546024:A>G showed strong association (β = 1.786, P-value = 2.56 × 10(-4)) with block-design test in the ERF study, while another variant rs1800273:G>A showed suggestive association (β = -0.465, P-value = 0.002) with Mini-Mental State Examination test in the RS. Both variants are highly conserved, although rs147546024:A>G is an intronic variant, whereas rs1800273:G>A is a missense variant in the DMD which has a predicted damaging effect on the protein. Further gene-based analysis of DMD revealed suggestive association (P-values = 0.087 and 0.074) with general cognitive ability in both cohorts. In conclusion, both single variant and gene-based analyses suggest the existence of variants in the DMD which may affect cognitive functioning in the general populations.
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Affiliation(s)
- Dina Vojinovic
- 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Clinic for Neurology and Psychiatry for Children and Youth, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Hieab H H Adams
- 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Department of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Sven J van der Lee
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Rutger Brouwer
- Center for Biomics, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Edwin Oole
- Center for Biomics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jeroen van Rooij
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Andre Uitterlinden
- 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands [3] Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Annemieke Aartsma-Rus
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - GertJan B van Ommen
- 1] Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands [2] Center of Medical Systems Biology, Leiden, The Netherlands
| | - M Arfan Ikram
- 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Department of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands [3] Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Cornelia M van Duijn
- 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Netherlands Consortium on Health Aging and National Genomics Initiative, Leiden, The Netherlands [3] Center of Medical Systems Biology, Leiden, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
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27
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Genome-wide analysis of multi-ancestry cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma. Nat Genet 2014; 46:1126-1130. [PMID: 25173106 PMCID: PMC4177225 DOI: 10.1038/ng.3087] [Citation(s) in RCA: 175] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2013] [Accepted: 08/07/2014] [Indexed: 12/13/2022]
Abstract
Elevated intraocular pressure (IOP) is an important risk factor in developing glaucoma and IOP variability may herald glaucomatous development or progression. We report the results of a genome-wide association study meta-analysis of 18 population cohorts from the International Glaucoma Genetics Consortium (IGGC), comprising 35,296 multiethnic participants for IOP. We confirm genetic association of known loci for IOP and primary open angle glaucoma (POAG) and identify four new IOP loci located on chromosome 3q25.31 within the FNDC3B gene (p=4.19×10−08 for rs6445055), two on chromosome 9 (p=2.80×10−11 for rs2472493 near ABCA1 and p=6.39×10−11 for rs8176693 within ABO) and one on chromosome 11p11.2 (best p=1.04×10−11 for rs747782). Separate meta-analyses of four independent POAG cohorts, totaling 4,284 cases and 95,560 controls, show that three of these IOP loci are also associated with POAG.
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28
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Abstract
The heritability of borderline personality (BP) features has been established in multiple twin and family studies. Using data from the borderline subscale of the Personality Assessment Inventory Borderline Features Scale (PAI-BOR) collected in two Dutch cohorts (N=7125), the Netherlands Twin Register and The Netherlands Study of Depression and Anxiety, we show that heritability of the PAI-BOR total score using genome-wide single-nucleotide polymorphism (SNPs) is estimated at 23%, and that the genetic variance is substantially higher in affect instability items compared with the other three subscales of the PAI-BOR (42.7% vs non-significant estimates for self-harm, negative relations and identity problems). We present results from a first genome-wide association study of BP features, which shows a promising signal on chromosome 5 corresponding to SERINC5, a protein involved in myelination. Reduced myelination has been suggested as possibly having a role in the development of psychiatric disorders characterized by lack of social interaction. The signal was confirmed in a third independent Dutch cohort drawn from the Erasmus Rucphen Family study (N=1301). Our analyses were complemented by investigating the heterogeneity that was implied by the differences in genetic variance components in the four subscales of the PAI-BOR. These analyses show that the association of SNPs tagging SERINC5 differs substantially across the 24 items of the PAI-BOR. Further, using reverse regression we showed that the effects were present only in subjects with higher scores on the PAI-BOR. Taken together, these results suggest that future genome-wide analyses can benefit substantially by taking into account the phenotypic and genetic heterogeneity of BP features.
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29
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Pirastu N, Kooyman M, Traglia M, Robino A, Willems SM, Pistis G, d’Adamo P, Amin N, d’Eustacchio A, Navarini L, Sala C, Karssen LC, van Duijn C, Toniolo D, Gasparini P. Association analysis of bitter receptor genes in five isolated populations identifies a significant correlation between TAS2R43 variants and coffee liking. PLoS One 2014; 9:e92065. [PMID: 24647340 PMCID: PMC3960174 DOI: 10.1371/journal.pone.0092065] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Accepted: 02/19/2014] [Indexed: 01/20/2023] Open
Abstract
Coffee, one of the most popular beverages in the world, contains many different physiologically active compounds with a potential impact on people’s health. Despite the recent attention given to the genetic basis of its consumption, very little has been done in understanding genes influencing coffee preference among different individuals. Given its markedly bitter taste, we decided to verify if bitter receptor genes (TAS2Rs) variants affect coffee liking. In this light, 4066 people from different parts of Europe and Central Asia filled in a field questionnaire on coffee liking. They have been consequently recruited and included in the study. Eighty-eight SNPs covering the 25 TAS2R genes were selected from the available imputed ones and used to run association analysis for coffee liking. A significant association was detected with three SNP: one synonymous and two functional variants (W35S and H212R) on the TAS2R43 gene. Both variants have been shown to greatly reduce in vitro protein activity. Surprisingly the wild type allele, which corresponds to the functional form of the protein, is associated to higher liking of coffee. Since the hTAS2R43 receptor is sensible to caffeine, we verified if the detected variants produced differences in caffeine bitter perception on a subsample of people coming from the FVG cohort. We found a significant association between differences in caffeine perception and the H212R variant but not with the W35S, which suggests that the effect of the TAS2R43 gene on coffee liking is mediated by caffeine and in particular by the H212R variant. No other significant association was found with other TAS2R genes. In conclusion, the present study opens new perspectives in the understanding of coffee liking. Further studies are needed to clarify the role of the TAS2R43 gene in coffee hedonics and to identify which other genes and pathways are involved in its genetics.
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Affiliation(s)
- Nicola Pirastu
- Institute for Maternal and Child Health, Istituto Di Ricovero e Cura a Carattere Scientifico “Burlo Garofolo,” Trieste, Italy
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
- * E-mail:
| | - Maarten Kooyman
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Antonietta Robino
- Institute for Maternal and Child Health, Istituto Di Ricovero e Cura a Carattere Scientifico “Burlo Garofolo,” Trieste, Italy
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Sara M. Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Giorgio Pistis
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Pio d’Adamo
- Institute for Maternal and Child Health, Istituto Di Ricovero e Cura a Carattere Scientifico “Burlo Garofolo,” Trieste, Italy
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Angela d’Eustacchio
- Institute for Maternal and Child Health, Istituto Di Ricovero e Cura a Carattere Scientifico “Burlo Garofolo,” Trieste, Italy
| | | | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Lennart C. Karssen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Cornelia van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy
| | - Paolo Gasparini
- Institute for Maternal and Child Health, Istituto Di Ricovero e Cura a Carattere Scientifico “Burlo Garofolo,” Trieste, Italy
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
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30
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van den Berg L, Henneman P, Willems van Dijk K, Delemarre-van de Waal HA, Oostra BA, van Duijn CM, Janssens ACJW. Heritability of dietary food intake patterns. Acta Diabetol 2013; 50:721-6. [PMID: 22415036 PMCID: PMC3898132 DOI: 10.1007/s00592-012-0387-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2011] [Accepted: 02/27/2012] [Indexed: 11/18/2022]
Abstract
The quality and quantity of food intake affect body weight, but little is known about the genetics of such human dietary intake patterns in relation to the genetics of BMI. We aimed to estimate the heritability of dietary intake patterns and genetic correlation with BMI in participants of the Erasmus Rucphen Family study. The study included 1,690 individuals (42 % men; age range, 19-92), of whom 41.4 % were overweight and 15.9 % were obese. Self-report questionnaires were used to assess the number of days (0-7) on which participants consumed vegetables, fruit, fruit juice, fish, unhealthy snacks, fastfood, and soft drinks. Principal component analysis was applied to examine the correlations between the questionnaire items and to generate dietary intake pattern scores. Heritability and the shared genetic and shared non-genetic (environmental) correlations were estimated using the family structure of the cohort. Principal component analysis suggested that the questionnaire items could be grouped in a healthy and unhealthy dietary intake pattern, explaining 22 and 18 % of the phenotypic variance, respectively. The dietary intake patterns had a heritability of 0.32 for the healthy and 0.27 for the unhealthy pattern. Genetic correlations between the dietary intake patterns and BMI were not significant, but we found a significant environmental correlation between the unhealthy dietary intake pattern and BMI. Specific dietary intake patterns are associated with the risk of obesity and are heritable traits. The genetic factors that determine specific dietary intake patterns do not significantly overlap with the genetic factors that determine BMI.
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Affiliation(s)
- Linda van den Berg
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pediatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of General Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Cornelia M. van Duijn
- Genetic-Epidemiology Unit, Department of Epidemiology and Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands
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31
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Cheng CY, Schache M, Ikram M, Young T, Guggenheim J, Vitart V, MacGregor S, Verhoeven V, Barathi V, Liao J, Hysi P, Bailey-Wilson J, St. Pourcain B, Kemp J, McMahon G, Timpson N, Evans D, Montgomery G, Mishra A, Wang Y, Wang J, Rochtchina E, Polasek O, Wright A, Amin N, van Leeuwen E, Wilson J, Pennell C, van Duijn C, de Jong P, Vingerling J, Zhou X, Chen P, Li R, Tay WT, Zheng Y, Chew M, Burdon KP, Craig JE, Iyengar SK, Igo RP, Lass JH, Chew EY, Haller T, Mihailov E, Metspalu A, Wedenoja J, Simpson CL, Wojciechowski R, Höhn R, Mirshahi A, Zeller T, Pfeiffer N, Lackner KJ, Bettecken T, Meitinger T, Oexle K, Pirastu M, Portas L, Nag A, Williams KM, Yonova-Doing E, Klein R, Klein BE, Hosseini SM, Paterson AD, Makela KM, Lehtimaki T, Kahonen M, Raitakari O, Yoshimura N, Matsuda F, Chen LJ, Pang CP, Yip SP, Yap MK, Meguro A, Mizuki N, Inoko H, Foster PJ, Zhao JH, Vithana E, Tai ES, Fan Q, Xu L, Campbell H, Fleck B, Rudan I, Aung T, Hofman A, Uitterlinden AG, Bencic G, Khor CC, Forward H, Pärssinen O, Mitchell P, Rivadeneira F, Hewitt AW, Williams C, Oostra BA, Teo YY, Hammond CJ, Stambolian D, Mackey DA, Klaver CC, Wong TY, Saw SM, Baird PN. Nine loci for ocular axial length identified through genome-wide association studies, including shared loci with refractive error. Am J Hum Genet 2013; 93:264-77. [PMID: 24144296 PMCID: PMC3772747 DOI: 10.1016/j.ajhg.2013.06.016] [Citation(s) in RCA: 113] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2013] [Revised: 04/17/2013] [Accepted: 06/12/2013] [Indexed: 01/15/2023] Open
Abstract
Refractive errors are common eye disorders of public health importance worldwide. Ocular axial length (AL) is the major determinant of refraction and thus of myopia and hyperopia. We conducted a meta-analysis of genome-wide association studies for AL, combining 12,531 Europeans and 8,216 Asians. We identified eight genome-wide significant loci for AL (RSPO1, C3orf26, LAMA2, GJD2, ZNRF3, CD55, MIP, and ALPPL2) and confirmed one previously reported AL locus (ZC3H11B). Of the nine loci, five (LAMA2, GJD2, CD55, ALPPL2, and ZC3H11B) were associated with refraction in 18 independent cohorts (n = 23,591). Differential gene expression was observed for these loci in minus-lens-induced myopia mouse experiments and human ocular tissues. Two of the AL genes, RSPO1 and ZNRF3, are involved in Wnt signaling, a pathway playing a major role in the regulation of eyeball size. This study provides evidence of shared genes between AL and refraction, but importantly also suggests that these traits may have unique pathways.
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Affiliation(s)
- Ching-Yu Cheng
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Centre for Quantitative Medicine, Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore
| | - Maria Schache
- Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia
| | - M. Kamran Ikram
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Centre for Quantitative Medicine, Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Terri L. Young
- Department of Ophthalmology, Duke University Medical Center, Durham, NC 27710, USA
- Division of Neuroscience and Behavioural Disorders, Duke-National University of Singapore, Graduate Medical School, Singapore 169857, Singapore
| | - Jeremy A. Guggenheim
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Stuart MacGregor
- Queensland Institute of Medical Research, Brisbane, QLD 4029, Australia
| | - Virginie J.M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Veluchamy A. Barathi
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore
| | - Jiemin Liao
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London SE1 7EH, UK
| | - Joan E. Bailey-Wilson
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, USA
| | - Beate St. Pourcain
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - John P. Kemp
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - George McMahon
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - Nicholas J. Timpson
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - David M. Evans
- MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | | | - Aniket Mishra
- Queensland Institute of Medical Research, Brisbane, QLD 4029, Australia
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital University of Medical Science, Beijing 100730, China
| | - Jie Jin Wang
- Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia
- Department of Ophthalmology, Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, NSW 2145, Australia
| | - Elena Rochtchina
- Department of Ophthalmology, Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, NSW 2145, Australia
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Croatia, Split 21000, Croatia
| | - Alan F. Wright
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | | | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Craig E. Pennell
- School of Women’s and Infants’ Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Paulus T.V.M. de Jong
- Netherlands Institute of Neuroscience (NIN), An Institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam 1105 BA, the Netherlands
- Department of Ophthalmology, Academisch Medisch Centrum, Amsterdam 1105 AZ, the Netherlands and Leids Universitair Medisch Centrum, Leiden 2300 RC, the Netherlands
| | - Johannes R. Vingerling
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Xin Zhou
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
| | - Peng Chen
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
| | - Ruoying Li
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
| | - Wan-Ting Tay
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Yingfeng Zheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Merwyn Chew
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Kathryn P. Burdon
- Department of Ophthalmology, Flinders University, Adelaide, SA 5001, Australia
| | - Jamie E. Craig
- Department of Ophthalmology, Flinders University, Adelaide, SA 5001, Australia
| | - Sudha K. Iyengar
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, OH 44106, USA
- Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, USA
- Center for Clinical Investigation, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Robert P. Igo
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Jonathan H. Lass
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, OH 44106, USA
| | - Emily Y. Chew
- National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Juho Wedenoja
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki 00014, Finland
| | - Claire L. Simpson
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, USA
| | - Robert Wojciechowski
- Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - René Höhn
- Department of Ophthalmology, University Medical Center Mainz, Mainz 55131, Germany
| | - Alireza Mirshahi
- Department of Ophthalmology, University Medical Center Mainz, Mainz 55131, Germany
| | - Tanja Zeller
- Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg 20246, Germany
| | - Norbert Pfeiffer
- Department of Ophthalmology, University Medical Center Mainz, Mainz 55131, Germany
| | - Karl J. Lackner
- Department of Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Mainz 55131, Germany
| | - Thomas Bettecken
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg 85764, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg 85764, Germany
- Institute of Human Genetics, Technical University Munich, Munich 81675, Germany
| | - Konrad Oexle
- Institute of Human Genetics, Technical University Munich, Munich 81675, Germany
| | - Mario Pirastu
- Institute of Population Genetics, National Research Council of Italy, Sassari 07100, Italy
| | - Laura Portas
- Institute of Population Genetics, National Research Council of Italy, Sassari 07100, Italy
| | - Abhishek Nag
- Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London SE1 7EH, UK
| | - Katie M. Williams
- Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London SE1 7EH, UK
| | - Ekaterina Yonova-Doing
- Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London SE1 7EH, UK
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
| | - Barbara E. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
| | - S. Mohsen Hosseini
- Program in Genetics and Genome Biology, The Hospital for Sick Children and Institute for Medical Sciences, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children and Institute for Medical Sciences, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Kari-Matti Makela
- Department of Clinical Chemistry, Filmlab Laboratories, Tampere University Hospital and School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Terho Lehtimaki
- Department of Clinical Chemistry, Filmlab Laboratories, Tampere University Hospital and School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Mika Kahonen
- Department of Clinical Physiology, Tampere University Hospital and School of Medicine, University of Tampere, Tampere 33521, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, and Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20041, Finland
| | - Nagahisa Yoshimura
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Fumihiko Matsuda
- Department of Human Disease Genomics, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
| | - Li Jia Chen
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Chi Pui Pang
- Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Eye Hospital, Kowloon, Hong Kong
| | - Shea Ping Yip
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Maurice K.H. Yap
- Centre for Myopia Research, School of Optometry, Hong Kong Polytechnic University, Kowloon, Hong Kong
| | - Akira Meguro
- Department of Ophthalmology and Visual Sciences, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Japan
| | - Nobuhisa Mizuki
- Department of Ophthalmology and Visual Sciences, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Japan
| | - Hidetoshi Inoko
- Department of Genetic Information, Division of Molecular Life Science, Tokai University School of Medicine, Kanagawa 259-1193, Japan
| | - Paul J. Foster
- NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology, London EC1V 2PD, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Sciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Eranga Vithana
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore
- Department of Medicine, National University of Singapore and National University Health System, Singapore 119228, Singapore
| | - Qiao Fan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
| | - Liang Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital University of Medical Science, Beijing 100730, China
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Brian Fleck
- Princess Alexandra Eye Pavilion, Edinburgh EH3 9HA, UK
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Tin Aung
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Goran Bencic
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb 10000, Croatia
| | - Chiea-Chuen Khor
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Hannah Forward
- School of Women’s and Infants’ Health, The University of Western Australia, Perth, WA 6009, Australia
| | - Olavi Pärssinen
- Department of Health Sciences and Gerontology Research Center, University of Jyväskylä, Jyväskylä 40014, Finland
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä 40620, Finland
| | - Paul Mitchell
- Department of Ophthalmology, Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, NSW 2145, Australia
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Alex W. Hewitt
- Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, WA 6009, Australia
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, Singapore
| | - Christopher J. Hammond
- Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London SE1 7EH, UK
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David A. Mackey
- Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, WA 6009, Australia
| | - Caroline C.W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000 CA, the Netherlands
| | - Tien-Yin Wong
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Seang-Mei Saw
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117597, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Centre for Quantitative Medicine, Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore
| | - Paul N. Baird
- Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, VIC 3002, Australia
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Belonogova NM, Svishcheva GR, van Duijn CM, Aulchenko YS, Axenovich TI. Region-based association analysis of human quantitative traits in related individuals. PLoS One 2013; 8:e65395. [PMID: 23799013 PMCID: PMC3684601 DOI: 10.1371/journal.pone.0065395] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2013] [Accepted: 04/24/2013] [Indexed: 01/27/2023] Open
Abstract
Regional-based association analysis instead of individual testing of each SNP was introduced in genome-wide association studies to increase the power of gene mapping, especially for rare genetic variants. For regional association tests, the kernel machine-based regression approach was recently proposed as a more powerful alternative to collapsing-based methods. However, the vast majority of existing algorithms and software for the kernel machine-based regression are applicable only to unrelated samples. In this paper, we present a new method for the kernel machine-based regression association analysis of quantitative traits in samples of related individuals. The method is based on the GRAMMAR+ transformation of phenotypes of related individuals, followed by use of existing kernel machine-based regression software for unrelated samples. We compared the performance of kernel-based association analysis on the material of the Genetic Analysis Workshop 17 family sample and real human data by using our transformation, the original untransformed trait, and environmental residuals. We demonstrated that only the GRAMMAR+ transformation produced type I errors close to the nominal value and that this method had the highest empirical power. The new method can be applied to analysis of related samples by using existing software for kernel-based association analysis developed for unrelated samples.
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Affiliation(s)
- Nadezhda M. Belonogova
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Gulnara R. Svishcheva
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | | | - Yurii S. Aulchenko
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Tatiana I. Axenovich
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
- * E-mail:
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Meta-analysis of telomere length in 19,713 subjects reveals high heritability, stronger maternal inheritance and a paternal age effect. Eur J Hum Genet 2013; 21:1163-8. [PMID: 23321625 DOI: 10.1038/ejhg.2012.303] [Citation(s) in RCA: 320] [Impact Index Per Article: 29.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2012] [Revised: 11/08/2012] [Accepted: 11/13/2012] [Indexed: 02/08/2023] Open
Abstract
Telomere length (TL) has been associated with aging and mortality, but individual differences are also influenced by genetic factors, with previous studies reporting heritability estimates ranging from 34 to 82%. Here we investigate the heritability, mode of inheritance and the influence of parental age at birth on TL in six large, independent cohort studies with a total of 19,713 participants. The meta-analysis estimate of TL heritability was 0.70 (95% CI 0.64-0.76) and is based on a pattern of results that is highly similar for twins and other family members. We observed a stronger mother-offspring (r=0.42; P-value=3.60 × 10(-61)) than father-offspring correlation (r=0.33; P-value=7.01 × 10(-5)), and a significant positive association with paternal age at offspring birth (β=0.005; P-value=7.01 × 10(-5)). Interestingly, a significant and quite substantial correlation in TL between spouses (r=0.25; P-value=2.82 × 10(-30)) was seen, which appeared stronger in older spouse pairs (mean age ≥55 years; r=0.31; P-value=4.27 × 10(-23)) than in younger pairs (mean age<55 years; r=0.20; P-value=3.24 × 10(-10)). In summary, we find a high and very consistent heritability estimate for TL, evidence for a maternal inheritance component and a positive association with paternal age.
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34
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Amin N, Hottenga JJ, Hansell NK, Janssens ACJW, de Moor MHM, Madden PAF, Zorkoltseva IV, Penninx BW, Terracciano A, Uda M, Tanaka T, Esko T, Realo A, Ferrucci L, Luciano M, Davies G, Metspalu A, Abecasis GR, Deary IJ, Raikkonen K, Bierut LJ, Costa PT, Saviouk V, Zhu G, Kirichenko AV, Isaacs A, Aulchenko YS, Willemsen G, Heath AC, Pergadia ML, Medland SE, Axenovich TI, de Geus E, Montgomery GW, Wright MJ, Oostra BA, Martin NG, Boomsma DI, van Duijn CM. Refining genome-wide linkage intervals using a meta-analysis of genome-wide association studies identifies loci influencing personality dimensions. Eur J Hum Genet 2012; 21:876-82. [PMID: 23211697 DOI: 10.1038/ejhg.2012.263] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2011] [Revised: 09/21/2012] [Accepted: 10/26/2012] [Indexed: 11/10/2022] Open
Abstract
Personality traits are complex phenotypes related to psychosomatic health. Individually, various gene finding methods have not achieved much success in finding genetic variants associated with personality traits. We performed a meta-analysis of four genome-wide linkage scans (N=6149 subjects) of five basic personality traits assessed with the NEO Five-Factor Inventory. We compared the significant regions from the meta-analysis of linkage scans with the results of a meta-analysis of genome-wide association studies (GWAS) (N∼17 000). We found significant evidence of linkage of neuroticism to chromosome 3p14 (rs1490265, LOD=4.67) and to chromosome 19q13 (rs628604, LOD=3.55); of extraversion to 14q32 (ATGG002, LOD=3.3); and of agreeableness to 3p25 (rs709160, LOD=3.67) and to two adjacent regions on chromosome 15, including 15q13 (rs970408, LOD=4.07) and 15q14 (rs1055356, LOD=3.52) in the individual scans. In the meta-analysis, we found strong evidence of linkage of extraversion to 4q34, 9q34, 10q24 and 11q22, openness to 2p25, 3q26, 9p21, 11q24, 15q26 and 19q13 and agreeableness to 4q34 and 19p13. Significant evidence of association in the GWAS was detected between openness and rs677035 at 11q24 (P-value=2.6 × 10(-06), KCNJ1). The findings of our linkage meta-analysis and those of the GWAS suggest that 11q24 is a susceptible locus for openness, with KCNJ1 as the possible candidate gene.
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Affiliation(s)
- Najaf Amin
- Unit of Genetic Epidemiology, Department of Epidemiology and Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands
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Svishcheva GR, Axenovich TI, Belonogova NM, van Duijn CM, Aulchenko YS. Rapid variance components-based method for whole-genome association analysis. Nat Genet 2012; 44:1166-70. [PMID: 22983301 DOI: 10.1038/ng.2410] [Citation(s) in RCA: 133] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2011] [Accepted: 08/16/2012] [Indexed: 11/09/2022]
Abstract
The variance component tests used in genome-wide association studies (GWAS) including large sample sizes become computationally exhaustive when the number of genetic markers is over a few hundred thousand. We present an extremely fast variance components-based two-step method, GRAMMAR-Gamma, developed as an analytical approximation within a framework of the score test approach. Using simulated and real human GWAS data sets, we show that this method provides unbiased estimates of the SNP effect and has a power close to that of the likelihood ratio test-based method. The computational complexity of our method is close to its theoretical minimum, that is, to the complexity of the analysis that ignores genetic structure. The running time of our method linearly depends on sample size, whereas this dependency is quadratic for other existing methods. Simulations suggest that GRAMMAR-Gamma may be used for association testing in whole-genome resequencing studies of large human cohorts.
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Affiliation(s)
- Gulnara R Svishcheva
- Institute of Cytology and Genetics, Siberian Division of the Russian Academy of Sciences, Novosibirsk, Russia
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Abstract
Personality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17,375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ≈ 2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10(-8) and 3.1 × 10(-8)) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10(-8)). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.
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Dissecting the genetic make-up of North-East Sardinia using a large set of haploid and autosomal markers. Eur J Hum Genet 2012; 20:956-64. [PMID: 22378280 DOI: 10.1038/ejhg.2012.22] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Sardinia has been used for genetic studies because of its historical isolation, genetic homogeneity and increased prevalence of certain rare diseases. Controversy remains concerning the genetic substructure and the extent of genetic homogeneity, which has implications for the design of genome-wide association studies (GWAS). We revisited this issue by examining the genetic make-up of a sample from North-East Sardinia using a dense set of autosomal, Y chromosome and mitochondrial markers to assess the potential of the sample for GWAS and fine mapping studies. We genotyped individuals for 500K single-nucleotide polymorphisms, Y chromosome markers and sequenced the mitochondrial hypervariable (HVI-HVII) regions. We identified major haplogroups and compared these with other populations. We estimated linkage disequilibrium (LD) and haplotype diversity across autosomal markers, and compared these with other populations. Our results show that within Sardinia there is no major population substructure and thus it can be considered a genetically homogenous population. We did not find substantial differences in the extent of LD in Sardinians compared with other populations. However, we showed that at least 9% of genomic regions in Sardinians differed in LD structure, which is helpful for identifying functional variants using fine mapping. We concluded that Sardinia is a powerful setting for genetic studies including GWAS and other mapping approaches.
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The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data. Transl Psychiatry 2011; 1:e50. [PMID: 22833196 PMCID: PMC3309491 DOI: 10.1038/tp.2011.45] [Citation(s) in RCA: 85] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.
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Schuur M, Henneman P, van Swieten JC, Zillikens MC, de Koning I, Janssens ACJW, Witteman JCM, Aulchenko YS, Frants RR, Oostra BA, van Dijk KW, van Duijn CM. Insulin-resistance and metabolic syndrome are related to executive function in women in a large family-based study. Eur J Epidemiol 2010; 25:561-8. [PMID: 20585974 PMCID: PMC2921069 DOI: 10.1007/s10654-010-9476-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2010] [Accepted: 05/31/2010] [Indexed: 12/25/2022]
Abstract
While type 2 diabetes is well-known to be associated with poorer cognitive performance, few studies have reported on the association of metabolic syndrome (MetS) and contributing factors, such as insulin-resistance (HOMA-IR), low adiponectin-, and high C-reactive protein (CRP)- levels. We studied whether these factors are related to cognitive function and which of the MetS components are independently associated. The study was embedded in an ongoing family-based cohort study in a Dutch population. All participants underwent physical examinations, biomedical measurements, and neuropsychological testing. Linear regression models were used to determine the association between MetS, HOMA-IR, adiponectin levels, CRP, and cognitive test scores. Cross-sectional analyses were performed in 1,898 subjects (mean age 48 years, 43% men). People with MetS had significantly higher HOMA-IR scores, lower adiponectin levels, and higher CRP levels. MetS and high HOMA-IR were associated with poorer executive function in women (P = 0.03 and P = 0.009). MetS and HOMA-IR are associated with poorer executive function in women.
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Affiliation(s)
- M Schuur
- Genetic Epidemiology Unit Ee2173, Department of Epidemiology, Erasmus MC University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
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Ramdas WD, van Koolwijk LME, Ikram MK, Jansonius NM, de Jong PTVM, Bergen AAB, Isaacs A, Amin N, Aulchenko YS, Wolfs RCW, Hofman A, Rivadeneira F, Oostra BA, Uitterlinden AG, Hysi P, Hammond CJ, Lemij HG, Vingerling JR, Klaver CCW, van Duijn CM. A genome-wide association study of optic disc parameters. PLoS Genet 2010; 6:e1000978. [PMID: 20548946 PMCID: PMC2883590 DOI: 10.1371/journal.pgen.1000978] [Citation(s) in RCA: 168] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2009] [Accepted: 05/07/2010] [Indexed: 01/01/2023] Open
Abstract
The optic nerve head is involved in many ophthalmic disorders, including common diseases such as myopia and open-angle glaucoma. Two of the most important parameters are the size of the optic disc area and the vertical cup-disc ratio (VCDR). Both are highly heritable but genetically largely undetermined. We performed a meta-analysis of genome-wide association (GWA) data to identify genetic variants associated with optic disc area and VCDR. The gene discovery included 7,360 unrelated individuals from the population-based Rotterdam Study I and Rotterdam Study II cohorts. These cohorts revealed two genome-wide significant loci for optic disc area, rs1192415 on chromosome 1p22 (p = 6.72×10−19) within 117 kb of the CDC7 gene and rs1900004 on chromosome 10q21.3-q22.1 (p = 2.67×10−33) within 10 kb of the ATOH7 gene. They revealed two genome-wide significant loci for VCDR, rs1063192 on chromosome 9p21 (p = 6.15×10−11) in the CDKN2B gene and rs10483727 on chromosome 14q22.3-q23 (p = 2.93×10−10) within 40 kbp of the SIX1 gene. Findings were replicated in two independent Dutch cohorts (Rotterdam Study III and Erasmus Rucphen Family study; N = 3,612), and the TwinsUK cohort (N = 843). Meta-analysis with the replication cohorts confirmed the four loci and revealed a third locus at 16q12.1 associated with optic disc area, and four other loci at 11q13, 13q13, 17q23 (borderline significant), and 22q12.1 for VCDR. ATOH7 was also associated with VCDR independent of optic disc area. Three of the loci were marginally associated with open-angle glaucoma. The protein pathways in which the loci of optic disc area are involved overlap with those identified for VCDR, suggesting a common genetic origin. Morphologic characteristics of the optic nerve head are involved in many ophthalmic diseases. Its size, called the optic disc area, is an important measure and has been associated with e.g. myopia and open-angle glaucoma (OAG). Another important and clinical parameter of the optic disc is the vertical cup-disc ratio (VCDR). Although studies have shown a high heritability of optic disc area and VCDR, its genetic determinants are still undetermined. We therefore conducted a genome-wide association (GWA) study on these quantitative traits, using data of over 11,000 Caucasian participants, and related the findings to myopia and OAG. We found evidence for association of three loci with optic disc area: CDC7/TGFBR3 region, ATOH7, and SALL1; and six with VCDR: CDKN2B, SIX1, SCYL1, CHEK2, ATOH7, and DCLK1; and additionally one borderline significant locus: BCAS3. None of the loci could be related to myopia. There was marginal evidence for association of ATOH7, CDKN2B, and SIX1 with OAG, which remains to be confirmed. The present study reveals new insights into the physiological development of the optic nerve and may shed light on the pathophysiological protein pathways leading to (neuro-) ophthalmologic diseases such as OAG.
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Affiliation(s)
- Wishal D. Ramdas
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Leonieke M. E. van Koolwijk
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Glaucoma Service, The Rotterdam Eye Hospital, Rotterdam, The Netherlands
| | - M. Kamran Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Nomdo M. Jansonius
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Paulus T. V. M. de Jong
- Department of Ophthalmogenetics, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
| | - Arthur A. B. Bergen
- Department of Ophthalmogenetics, The Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Roger C. W. Wolfs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Andre G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Pirro Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Christopher J. Hammond
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Hans G. Lemij
- Glaucoma Service, The Rotterdam Eye Hospital, Rotterdam, The Netherlands
| | - Johannes R. Vingerling
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- * E-mail:
| | - Caroline C. W. Klaver
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
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Lee WJ, Pollin TI, O'Connell JR, Agarwala R, Schäffer AA. PedHunter 2.0 and its usage to characterize the founder structure of the Old Order Amish of Lancaster County. BMC MEDICAL GENETICS 2010; 11:68. [PMID: 20433770 PMCID: PMC2880975 DOI: 10.1186/1471-2350-11-68] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2009] [Accepted: 05/02/2010] [Indexed: 01/11/2023]
Abstract
BACKGROUND Because they are a closed founder population, the Old Order Amish (OOA) of Lancaster County have been the subject of many medical genetics studies. We constructed four versions of Anabaptist Genealogy Database (AGDB) using three sources of genealogies and multiple updates. In addition, we developed PedHunter, a suite of query software that can solve pedigree-related problems automatically and systematically. METHODS We report on how we have used new features in PedHunter to quantify the number and expected genetic contribution of founders to the OOA. The queries and utility of PedHunter programs are illustrated by examples using AGDB in this paper. For example, we calculated the number of founders expected to be contributing genetic material to the present-day living OOA and estimated the mean relative founder representation for each founder. New features in PedHunter also include pedigree trimming and pedigree renumbering, which should prove useful for studying large pedigrees. RESULTS With PedHunter version 2.0 querying AGDB version 4.0, we identified 34,160 presumed living OOA individuals and connected them into a 14-generation pedigree descending from 554 founders (332 females and 222 males) after trimming. From the analysis of cumulative mean relative founder representation, 128 founders (78 females and 50 males) accounted for over 95% of the mean relative founder contribution among living OOA descendants. DISCUSSION/CONCLUSIONS The OOA are a closed founder population in which a modest number of founders account for the genetic variation present in the current OOA population. Improvements to the PedHunter software will be useful in future studies of both the OOA and other populations with large and computerized genealogies.
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Affiliation(s)
- Woei-Jyh Lee
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894, USA
| | - Toni I Pollin
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, 660 W. Redwood Street, Baltimore, Maryland 21201, USA
| | - Jeffrey R O'Connell
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, 660 W. Redwood Street, Baltimore, Maryland 21201, USA
- Animal Improvement Programs Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Beltsville, Maryland 20705, USA
| | - Richa Agarwala
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894, USA
| | - Alejandro A Schäffer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, Maryland 20894, USA
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van der Loos MJHM, Koellinger PD, Groenen PJF, Thurik AR. Genome-wide association studies and the genetics of entrepreneurship. Eur J Epidemiol 2010; 25:1-3. [PMID: 20054611 PMCID: PMC2807937 DOI: 10.1007/s10654-009-9418-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2009] [Accepted: 12/15/2009] [Indexed: 11/30/2022]
Affiliation(s)
- Matthijs J H M van der Loos
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands.
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Henneman P, Aulchenko YS, Frants RR, Zorkoltseva IV, Zillikens MC, Frolich M, Oostra BA, van Dijk KW, van Duijn CM. Genetic architecture of plasma adiponectin overlaps with the genetics of metabolic syndrome-related traits. Diabetes Care 2010; 33:908-13. [PMID: 20067957 PMCID: PMC2845050 DOI: 10.2337/dc09-1385] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Adiponectin, a hormone secreted by adipose tissue, is of particular interest in metabolic syndrome, because it is inversely correlated with obesity and insulin sensitivity. However, it is not known to what extent the genetics of plasma adiponectin and the genetics of obesity and insulin sensitivity are interrelated. We aimed to evaluate the heritability of plasma adiponectin and its genetic correlation with the metabolic syndrome and metabolic syndrome-related traits and the association between these traits and 10 ADIPOQ single nucleotide polymorphisms (SNPs). RESEARCH DESIGN AND METHODS We made use of a family-based population, the Erasmus Rucphen Family study (1,258 women and 967 men). Heritability analysis was performed using a polygenic model. Genetic correlations were estimated using bivariate heritability analyses. Genetic association analysis was performed using a mixed model. RESULTS Plasma adiponectin showed a heritability of 55.1%. Genetic correlations between plasma adiponectin HDL cholesterol and plasma insulin ranged from 15 to 24% but were not significant for fasting glucose, triglycerides, blood pressure, homeostasis model assessment of insulin resistance (HOMA-IR), and C-reactive protein. A significant association with plasma adiponectin was found for ADIPOQ variants rs17300539 and rs182052. A nominally significant association was found with plasma insulin and HOMA-IR and ADIPOQ variant rs17300539 after adjustment for plasma adiponectin. CONCLUSIONS The significant genetic correlation between plasma adiponectin and HDL cholesterol and plasma insulin should be taken into account in the interpretation of genome-wide association studies. Association of ADIPOQ SNPs with plasma adiponectin was replicated, and we showed association between one ADIPOQ SNP and plasma insulin and HOMA-IR.
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Affiliation(s)
- Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
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Aulchenko YS, Struchalin MV, van Duijn CM. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 2010; 11:134. [PMID: 20233392 PMCID: PMC2846909 DOI: 10.1186/1471-2105-11-134] [Citation(s) in RCA: 361] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2009] [Accepted: 03/16/2010] [Indexed: 11/30/2022] Open
Abstract
Background Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, imputed single nucleotide polymorphisms (SNP) data are frequently used in GWA analyzes. Correct analysis of imputed data calls for the implementation of specific methods which take genotype imputation uncertainty into account. Results We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations. Conclusions ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci.
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Affiliation(s)
- Yurii S Aulchenko
- Department of Epidemiology, Erasmus MC, Postbus 2040, 3000 CA Rotterdam, The Netherlands.
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Pattaro C, De Grandi A, Vitart V, Hayward C, Franke A, Aulchenko YS, Johansson A, Wild SH, Melville SA, Isaacs A, Polasek O, Ellinghaus D, Kolcic I, Nöthlings U, Zgaga L, Zemunik T, Gnewuch C, Schreiber S, Campbell S, Hastie N, Boban M, Meitinger T, Oostra BA, Riegler P, Minelli C, Wright AF, Campbell H, van Duijn CM, Gyllensten U, Wilson JF, Krawczak M, Rudan I, Pramstaller PP. A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level. BMC MEDICAL GENETICS 2010; 11:41. [PMID: 20222955 PMCID: PMC2848223 DOI: 10.1186/1471-2350-11-41] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2009] [Accepted: 03/11/2010] [Indexed: 11/10/2022]
Abstract
BACKGROUND Serum creatinine (S CR) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in S CR level is explicable by genetic factors. METHODS We performed a meta-analysis of genome-wide association studies of S CR undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence for an association with SCR (candidate loci) were replicated in two additional population-based samples ('replication cohorts'). RESULTS After the discovery meta-analysis, 29 loci were selected for replication. Association between SCR level and polymorphisms in the collagen type XXII alpha 1 (COL22A1) gene, on chromosome 8, and in the synaptotagmin-1 (SYT1) gene, on chromosome 12, were successfully replicated in the replication cohorts (p value = 1.0 x 10(-6) and 1.7 x 10(-4), respectively). Evidence of association was also found for polymorphisms in a locus including the gamma-aminobutyric acid receptor rho-2 (GABRR2) gene and the ubiquitin-conjugating enzyme E2-J1 (UBE2J1) gene (replication p value = 3.6 x 10(-3)). Previously reported findings, associating glomerular filtration rate with SNPs in the uromodulin (UMOD) gene and in the schroom family member 3 (SCHROOM3) gene were also replicated. CONCLUSIONS While confirming earlier results, our study provides new insights in the understanding of the genetic basis of serum creatinine regulatory processes. In particular, the association with the genes SYT1 and GABRR2 corroborate previous findings that highlighted a possible role of the neurotransmitters GABAA receptors in the regulation of the glomerular basement membrane and a possible interaction between GABAA receptors and synaptotagmin-I at the podocyte level.
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Affiliation(s)
- Cristian Pattaro
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University Lübeck, Lübeck, Germany
| | - Alessandro De Grandi
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University Lübeck, Lübeck, Germany
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Andre Franke
- Institute for Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Yurii S Aulchenko
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, 3000 CA Rotterdam, the Netherlands
| | - Asa Johansson
- Department of Genetics and Pathology, Rudbeck laboratory, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Sarah H Wild
- Centre for Population Health Sciences, University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK
| | - Scott A Melville
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University Lübeck, Lübeck, Germany
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, 3000 CA Rotterdam, the Netherlands
| | - Ozren Polasek
- Andrija Stampar School of Public Health, University of Zagreb Medical School, Rockefellerova 4, 10000 Zagreb, Croatia
- Gen-info Ltd, Ruzmarinka 17, 10000 Zagreb, Croatia
| | - David Ellinghaus
- Institute for Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Ivana Kolcic
- Andrija Stampar School of Public Health, University of Zagreb Medical School, Rockefellerova 4, 10000 Zagreb, Croatia
| | - Ute Nöthlings
- Popgen biobank, Christian-Albrechts-University Kiel, Kiel, Germany
- Institute for Experimental Medicine, Christian-Albrechts University Kiel, 24105 Kiel, Germany
| | - Lina Zgaga
- Andrija Stampar School of Public Health, University of Zagreb Medical School, Rockefellerova 4, 10000 Zagreb, Croatia
| | - Tatijana Zemunik
- Croatian Centre for Global Health, University of Split Medical School, Soltanska 2, 21000 Split, Croatia
| | - Carsten Gnewuch
- Institute for Clinical Chemistry and Laboratory Medicine, Regensburg University Medical Center, D-93053 Regensburg, Germany
| | - Stefan Schreiber
- Institute for Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Susan Campbell
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Nick Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Mladen Boban
- Croatian Centre for Global Health, University of Split Medical School, Soltanska 2, 21000 Split, Croatia
| | - Thomas Meitinger
- Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstr 1, D-85764 Neuherberg, Germany
| | - Ben A Oostra
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, 3000 CA Rotterdam, the Netherlands
| | - Peter Riegler
- Hemodialysis Unit, Hospital of Merano, Merano, Italy
| | - Cosetta Minelli
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University Lübeck, Lübeck, Germany
| | - Alan F Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, 3000 CA Rotterdam, the Netherlands
| | - Ulf Gyllensten
- Department of Genetics and Pathology, Rudbeck laboratory, Uppsala University, SE-751 85, Uppsala, Sweden
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK
| | - Michael Krawczak
- Popgen biobank, Christian-Albrechts-University Kiel, Kiel, Germany
- Institute of Medical Informatics and Statistics, Christian-Albrechts-University, Kiel, Germany
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK
- Gen-info Ltd, Ruzmarinka 17, 10000 Zagreb, Croatia
- Croatian Centre for Global Health, University of Split Medical School, Soltanska 2, 21000 Split, Croatia
| | - Peter P Pramstaller
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy - Affiliated Institute of the University Lübeck, Lübeck, Germany
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Department of Neurology, Central Hospital, Bolzano, Italy
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46
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Mascalzoni D, Janssens ACJW, Stewart A, Pramstaller P, Gyllensten U, Rudan I, van Duijn CM, Wilson JF, Campbell H, Quillan RMC. Comparison of participant information and informed consent forms of five European studies in genetic isolated populations. Eur J Hum Genet 2010; 18:296-302. [PMID: 19826451 PMCID: PMC2987217 DOI: 10.1038/ejhg.2009.155] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2008] [Revised: 08/24/2009] [Accepted: 08/28/2009] [Indexed: 11/09/2022] Open
Abstract
Family-based research in genetically isolated populations is an effective approach for identifying loci influencing variation in disease traits. In common with all studies in humans, those in genetically isolated populations need ethical approval; however, existing ethical frameworks may be inadequate to protect participant privacy and confidentiality and to address participants' information needs in such populations. Using the ethical-legal guidelines of the Council for International Organizations of Medical Sciences (CIOMS) as a template, we compared the participant information leaflets and consent forms of studies in five European genetically isolated populations to identify additional information that should be incorporated into information leaflets and consent forms to guarantee satisfactorily informed consent. We highlight the additional information that participants require on the research purpose and the reasons why their population was chosen; on the potential risks and benefits of participation; on the opportunities for benefit sharing; on privacy; on the withdrawal of consent and on the disclosure of genetic data. This research raises some important issues that should be addressed properly and identifies relevant types of information that should be incorporated into information leaflets for this type of study.
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Affiliation(s)
- Deborah Mascalzoni
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy.
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Belonogova NM, Axenovich TI, Aulchenko YS. A powerful genome-wide feasible approach to detect parent-of-origin effects in studies of quantitative traits. Eur J Hum Genet 2010; 18:379-84. [PMID: 19809476 PMCID: PMC2987227 DOI: 10.1038/ejhg.2009.167] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2008] [Revised: 07/20/2009] [Accepted: 09/01/2009] [Indexed: 11/09/2022] Open
Abstract
There is currently a lot of interest in the role of genomic imprinting in mammalian development. Many human diseases, such as cancer, obesity, diabetes and behavioral traits, may be related to imprinted genes. When searching for genes related to complex disorders, the power of genome-wide association analysis can be improved by introducing parent-of-origin effects into the analyses. For quantitative traits, family-based TDT analysis has successfully implemented such an approach. Although attractive for several reasons, TDT-based tests are known to be less powerful than methods based on measured genotype approaches. In this study, we describe a fast, powerful method for detecting parent-of-origin effects in studies of quantitative traits using a measured genotype framework. First, for each locus studied, we estimate the probabilities of an allele's parental origin using multipoint haplotype reconstruction. Next, we introduce the parental origin of these alleles as a covariate in regression models during the second step of GRAMMAR, a fast approximation to the measured genotype approach. We show that, compared with a TDT-based analysis, our method has a higher power to detect a locus exhibiting a parent-of-origin effect. Moreover, our method is applicable to a wider range of data, including pedigree structures that are not very informative for TDT. The method gives no false positives in the absence of parent-of-origin effects, under both additive and dominant models. As this method is an extension of the rapid GRAMMAR analysis, it is fast enough to be suitable for genome-wide association scans.
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Affiliation(s)
- Nadezhda M Belonogova
- Institute of Cytology & Genetics, Siberian Division of Russian Academy of Sciences (SD RAS), Novosibirsk, Russia
- Department of Cytology & Genetics, Novosibirsk State University, Novosibirsk, Russia
| | - Tatiana I Axenovich
- Institute of Cytology & Genetics, Siberian Division of Russian Academy of Sciences (SD RAS), Novosibirsk, Russia
- Department of Cytology & Genetics, Novosibirsk State University, Novosibirsk, Russia
| | - Yurii S Aulchenko
- Institute of Cytology & Genetics, Siberian Division of Russian Academy of Sciences (SD RAS), Novosibirsk, Russia
- Department of Epidemiology & Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands
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48
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Pecioska S, Zillikens MC, Henneman P, Snijders PJ, Oostra BA, van Duijn CM, Aulchenko YS. Association between type 2 diabetes loci and measures of fatness. PLoS One 2010; 5:e8541. [PMID: 20049090 PMCID: PMC2796390 DOI: 10.1371/journal.pone.0008541] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2008] [Accepted: 12/10/2009] [Indexed: 01/28/2023] Open
Abstract
Background Type 2 diabetes (T2D) is a metabolic disorder characterized by disturbances of carbohydrate, fat and protein metabolism and insulin resistance. The majority of T2D patients are obese and obesity by itself may be a cause of insulin resistance. Our aim was to evaluate whether the recently identified T2D risk alleles are associated with human measures of fatness as characterized with Dual Energy X-ray Absorptiometry (DEXA). Methodology/Principal Findings Genotypes and phenotypes of approximately 3,000 participants from cross-sectional ERF study were analyzed. Nine single nucleotide polymorphisms (SNPs) in CDKN2AB, CDKAL1, FTO, HHEX, IGF2BP2, KCNJ11, PPARG, SLC30A8 and TCF7L2 were genotyped. We used linear regression to study association between individual SNPs and the combined allelic risk score with body mass index (BMI), fat mass index (FMI), fat percentage (FAT), waist circumference (WC) and waist to hip ratio (WHR). Significant association was observed between rs8050136 (FTO) and BMI (p = 0.003), FMI (p = 0.007) and WC (p = 0.03); fat percentage was borderline significant (p = 0.053). No other SNPs alone or combined in a risk score demonstrated significant association to the measures of fatness. Conclusions/Significance From the recently identified T2D risk variants only the risk variant of the FTO gene (rs8050136) showed statistically significant association with BMI, FMI, and WC.
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Affiliation(s)
- Slavica Pecioska
- Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - M. Carola Zillikens
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Pieter J. Snijders
- Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ben A. Oostra
- Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Cornelia M. van Duijn
- Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Yurii S. Aulchenko
- Department of Epidemiology and Biostatistics and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
- Institute of Cytology and Genetics, SD RAS, Novosibirsk, Russia
- * E-mail:
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49
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Pasutto F, Matsumoto T, Mardin CY, Sticht H, Brandstätter JH, Michels-Rautenstrauss K, Weisschuh N, Gramer E, Ramdas WD, van Koolwijk LM, Klaver CC, Vingerling JR, Weber BH, Kruse FE, Rautenstrauss B, Barde YA, Reis A. Heterozygous NTF4 mutations impairing neurotrophin-4 signaling in patients with primary open-angle glaucoma. Am J Hum Genet 2009; 85:447-56. [PMID: 19765683 DOI: 10.1016/j.ajhg.2009.08.016] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2009] [Revised: 08/20/2009] [Accepted: 08/28/2009] [Indexed: 12/25/2022] Open
Abstract
Glaucoma, a main cause of blindness in the developed world, is characterized by progressive degeneration of retinal ganglion cells (RGCs), resulting in irreversible loss of vision. Although members of the neurotrophin gene family in various species are known to support the survival of numerous neuronal populations, including RGCs, it is less clear whether they are also required for survival and maintenance of adult neurons in humans. Here, we report seven different heterozygous mutations in the Neurotrophin-4 (NTF4) gene accounting for about 1.7% of primary open-angle glaucoma patients of European origin. Molecular modeling predicted a decreased affinity of neurotrophin 4 protein (NT-4) mutants with its specific tyrosine kinase receptor B (TrkB). Expression of recombinant NT-4 carrying the most frequent mutation was demonstrated to lead to decreased activation of TrkB. These findings suggest a pathway in the pathophysiology of glaucoma through loss of neurotrophic function and may eventually open the possibility of using ligands activating TrkB to prevent the progression of the disease.
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50
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Bellenguez C, Ober C, Bourgain C. A multiple splitting approach to linkage analysis in large pedigrees identifies a linkage to asthma on chromosome 12. Genet Epidemiol 2009; 33:207-16. [PMID: 18839415 DOI: 10.1002/gepi.20371] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Large genealogies are potentially very informative for linkage analysis. However, the software available for exact non-parametric multipoint linkage analysis is limited with respect to the complexity of the families it can handle. A solution is to split the large pedigrees into sub-families meeting complexity constraints. Different methods have been proposed to "best" split large genealogies. Here, we propose a new procedure in which linkage is performed on several carefully chosen sub-pedigree sets from the genealogy instead of using just a single sub-pedigree set. Our multiple splitting procedure capitalizes on the sensitivity of linkage results to family structure and has been designed to control computational feasibility and global type I error. We describe and apply this procedure to the extreme case of the highly complex Hutterite pedigree and use it to perform a genome-wide linkage analysis on asthma. The detection of a genome-wide significant linkage for asthma on chromosome 12q21 illustrates the potential of this multiple splitting approach.
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